cluster.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Clustering\n",
    "\n",
    "TODO: write.<br> \n",
    "Load (X, Y, F) for 6 tags 'python',... and apply Classification Pipelines.<br>\n",
    "Pipeline: (pca, lda, svd, nmf) --> (agglo, kmeans, lda, gmm, dbscan) --> plotgrid(decomp x clusteralgo). <br>\n",
    "Inputfiles are from ...nlpvec/ output is written to ...nlpvec/decomposition/ and ..nlpvec/clustering/. see decomposition and clustering\n",
    "\n",
    "| Name | Data Type                           | Description                             | Comment |\n",
    "|------| :---                                |-----------------------------------------|--------|\n",
    "| $s$  | $\\in \\mathbb{N}$                    | Number Samples                          | random 2000   |\n",
    "| $t$  | $\\in \\mathbb{N}$                    | Number of terms                         | reduced by projection |\n",
    "| $q$  | $\\in \\mathbb{S}$                    | Analysed tags (labels)                  | ['android'] |\n",
    "| $F$  | $\\in \\mathbb{S}^{t}_{q}$            | Feature names                           | useless     |\n",
    "| $Y$  | $\\in \\mathbb{B}^{s}_{q}$            | Actual classes                          | just for visualisations |\n",
    "| $X$  | $\\in \\mathbb{R}^{s \\times t}_{q}$   | tf-idf                                  | transformed  |\n",
    "\n",
    "\n",
    "find most simmilar to Y(q)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Decomposition\n",
    "TODO: write.<br> \n",
    "\n",
    "* $t \\in \\mathbb{N} \\longmapsto t_{r} \\in \\mathbb{N}$\n",
    "* $F \\in \\mathbb{S}^{t}_{q} \\longmapsto F \\in \\mathbb{S}^{t_{r}}_{q}$ \n",
    "* $X \\in \\mathbb{R}^{s \\times t}_{q} \\longmapsto X_{r} \\in \\mathbb{R}^{s \\times t_{r}}_{q}$\n",
    "\n",
    "internal dimension is for all projections the same,<br>\n",
    "but varies with cluster algo.\n",
    "most use 25, except DBscan, it used 5. Db scan has problems with dim > 50 in general.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>COMP</th>\n",
       "      <th>P</th>\n",
       "      <th>assertF</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>source</th>\n",
       "      <th>wordtype</th>\n",
       "      <th>vecimpl</th>\n",
       "      <th>htmlfeature</th>\n",
       "      <th>tf-idf</th>\n",
       "      <th>transformation</th>\n",
       "      <th>algo</th>\n",
       "      <th>dim</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"60\" valign=\"top\">stackoverflow</th>\n",
       "      <th rowspan=\"60\" valign=\"top\">lemma</th>\n",
       "      <th rowspan=\"60\" valign=\"top\">nltk</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">T</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">32</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">decomposition</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">LDA</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 1367)</td>\n",
       "      <td>(10214, 12)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 1367)</td>\n",
       "      <td>(10214, 16)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 1367)</td>\n",
       "      <td>(10214, 4)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 1367)</td>\n",
       "      <td>(10214, 6)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 1367)</td>\n",
       "      <td>(10214, 8)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">NMF</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 1367)</td>\n",
       "      <td>(10214, 12)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 1367)</td>\n",
       "      <td>(10214, 16)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 1367)</td>\n",
       "      <td>(10214, 4)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 1367)</td>\n",
       "      <td>(10214, 6)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 1367)</td>\n",
       "      <td>(10214, 8)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">PCA</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 1367)</td>\n",
       "      <td>(10214, 12)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 1367)</td>\n",
       "      <td>(10214, 16)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 1367)</td>\n",
       "      <td>(10214, 4)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 1367)</td>\n",
       "      <td>(10214, 6)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 1367)</td>\n",
       "      <td>(10214, 8)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SVD</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 1367)</td>\n",
       "      <td>(10214, 12)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 1367)</td>\n",
       "      <td>(10214, 16)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 1367)</td>\n",
       "      <td>(10214, 4)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 1367)</td>\n",
       "      <td>(10214, 6)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 1367)</td>\n",
       "      <td>(10214, 8)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"20\" valign=\"top\">TIB</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">32</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">decomposition</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">LDA</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 2549)</td>\n",
       "      <td>(21711, 12)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 2549)</td>\n",
       "      <td>(21711, 16)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">NMF</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 2549)</td>\n",
       "      <td>(21711, 12)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 2549)</td>\n",
       "      <td>(21711, 16)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">PCA</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 2549)</td>\n",
       "      <td>(21711, 12)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 2549)</td>\n",
       "      <td>(21711, 16)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SVD</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 2549)</td>\n",
       "      <td>(21711, 12)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 2549)</td>\n",
       "      <td>(21711, 16)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"20\" valign=\"top\">TIBC</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">32</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">decomposition</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">LDA</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 3257)</td>\n",
       "      <td>(23120, 12)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 3257)</td>\n",
       "      <td>(23120, 16)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">NMF</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 3257)</td>\n",
       "      <td>(23120, 12)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 3257)</td>\n",
       "      <td>(23120, 16)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">PCA</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 3257)</td>\n",
       "      <td>(23120, 12)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 3257)</td>\n",
       "      <td>(23120, 16)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SVD</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 3257)</td>\n",
       "      <td>(23120, 12)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 3257)</td>\n",
       "      <td>(23120, 16)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                 COMP  \\\n",
       "source        wordtype vecimpl htmlfeature tf-idf transformation algo dim               \n",
       "stackoverflow lemma    nltk    T           32     decomposition  LDA  12   (12, 1367)   \n",
       "                                                                      16   (16, 1367)   \n",
       "                                                                      4     (4, 1367)   \n",
       "                                                                      6     (6, 1367)   \n",
       "                                                                      8     (8, 1367)   \n",
       "                                                                 NMF  12   (12, 1367)   \n",
       "                                                                      16   (16, 1367)   \n",
       "                                                                      4     (4, 1367)   \n",
       "                                                                      6     (6, 1367)   \n",
       "                                                                      8     (8, 1367)   \n",
       "                                                                 PCA  12   (12, 1367)   \n",
       "                                                                      16   (16, 1367)   \n",
       "                                                                      4     (4, 1367)   \n",
       "                                                                      6     (6, 1367)   \n",
       "                                                                      8     (8, 1367)   \n",
       "                                                                 SVD  12   (12, 1367)   \n",
       "                                                                      16   (16, 1367)   \n",
       "                                                                      4     (4, 1367)   \n",
       "                                                                      6     (6, 1367)   \n",
       "                                                                      8     (8, 1367)   \n",
       "                               TIB         32     decomposition  LDA  12   (12, 2549)   \n",
       "                                                                      16   (16, 2549)   \n",
       "                                                                      4             -   \n",
       "                                                                      6             -   \n",
       "                                                                      8             -   \n",
       "                                                                 NMF  12   (12, 2549)   \n",
       "                                                                      16   (16, 2549)   \n",
       "                                                                      4             -   \n",
       "                                                                      6             -   \n",
       "                                                                      8             -   \n",
       "                                                                 PCA  12   (12, 2549)   \n",
       "                                                                      16   (16, 2549)   \n",
       "                                                                      4             -   \n",
       "                                                                      6             -   \n",
       "                                                                      8             -   \n",
       "                                                                 SVD  12   (12, 2549)   \n",
       "                                                                      16   (16, 2549)   \n",
       "                                                                      4             -   \n",
       "                                                                      6             -   \n",
       "                                                                      8             -   \n",
       "                               TIBC        32     decomposition  LDA  12   (12, 3257)   \n",
       "                                                                      16   (16, 3257)   \n",
       "                                                                      4             -   \n",
       "                                                                      6             -   \n",
       "                                                                      8             -   \n",
       "                                                                 NMF  12   (12, 3257)   \n",
       "                                                                      16   (16, 3257)   \n",
       "                                                                      4             -   \n",
       "                                                                      6             -   \n",
       "                                                                      8             -   \n",
       "                                                                 PCA  12   (12, 3257)   \n",
       "                                                                      16   (16, 3257)   \n",
       "                                                                      4             -   \n",
       "                                                                      6             -   \n",
       "                                                                      8             -   \n",
       "                                                                 SVD  12   (12, 3257)   \n",
       "                                                                      16   (16, 3257)   \n",
       "                                                                      4             -   \n",
       "                                                                      6             -   \n",
       "                                                                      8             -   \n",
       "\n",
       "                                                                                     P  \\\n",
       "source        wordtype vecimpl htmlfeature tf-idf transformation algo dim                \n",
       "stackoverflow lemma    nltk    T           32     decomposition  LDA  12   (10214, 12)   \n",
       "                                                                      16   (10214, 16)   \n",
       "                                                                      4     (10214, 4)   \n",
       "                                                                      6     (10214, 6)   \n",
       "                                                                      8     (10214, 8)   \n",
       "                                                                 NMF  12   (10214, 12)   \n",
       "                                                                      16   (10214, 16)   \n",
       "                                                                      4     (10214, 4)   \n",
       "                                                                      6     (10214, 6)   \n",
       "                                                                      8     (10214, 8)   \n",
       "                                                                 PCA  12   (10214, 12)   \n",
       "                                                                      16   (10214, 16)   \n",
       "                                                                      4     (10214, 4)   \n",
       "                                                                      6     (10214, 6)   \n",
       "                                                                      8     (10214, 8)   \n",
       "                                                                 SVD  12   (10214, 12)   \n",
       "                                                                      16   (10214, 16)   \n",
       "                                                                      4     (10214, 4)   \n",
       "                                                                      6     (10214, 6)   \n",
       "                                                                      8     (10214, 8)   \n",
       "                               TIB         32     decomposition  LDA  12   (21711, 12)   \n",
       "                                                                      16   (21711, 16)   \n",
       "                                                                      4              -   \n",
       "                                                                      6              -   \n",
       "                                                                      8              -   \n",
       "                                                                 NMF  12   (21711, 12)   \n",
       "                                                                      16   (21711, 16)   \n",
       "                                                                      4              -   \n",
       "                                                                      6              -   \n",
       "                                                                      8              -   \n",
       "                                                                 PCA  12   (21711, 12)   \n",
       "                                                                      16   (21711, 16)   \n",
       "                                                                      4              -   \n",
       "                                                                      6              -   \n",
       "                                                                      8              -   \n",
       "                                                                 SVD  12   (21711, 12)   \n",
       "                                                                      16   (21711, 16)   \n",
       "                                                                      4              -   \n",
       "                                                                      6              -   \n",
       "                                                                      8              -   \n",
       "                               TIBC        32     decomposition  LDA  12   (23120, 12)   \n",
       "                                                                      16   (23120, 16)   \n",
       "                                                                      4              -   \n",
       "                                                                      6              -   \n",
       "                                                                      8              -   \n",
       "                                                                 NMF  12   (23120, 12)   \n",
       "                                                                      16   (23120, 16)   \n",
       "                                                                      4              -   \n",
       "                                                                      6              -   \n",
       "                                                                      8              -   \n",
       "                                                                 PCA  12   (23120, 12)   \n",
       "                                                                      16   (23120, 16)   \n",
       "                                                                      4              -   \n",
       "                                                                      6              -   \n",
       "                                                                      8              -   \n",
       "                                                                 SVD  12   (23120, 12)   \n",
       "                                                                      16   (23120, 16)   \n",
       "                                                                      4              -   \n",
       "                                                                      6              -   \n",
       "                                                                      8              -   \n",
       "\n",
       "                                                                           assertF  \n",
       "source        wordtype vecimpl htmlfeature tf-idf transformation algo dim           \n",
       "stackoverflow lemma    nltk    T           32     decomposition  LDA  12   (1367,)  \n",
       "                                                                      16   (1367,)  \n",
       "                                                                      4    (1367,)  \n",
       "                                                                      6    (1367,)  \n",
       "                                                                      8    (1367,)  \n",
       "                                                                 NMF  12   (1367,)  \n",
       "                                                                      16   (1367,)  \n",
       "                                                                      4    (1367,)  \n",
       "                                                                      6    (1367,)  \n",
       "                                                                      8    (1367,)  \n",
       "                                                                 PCA  12   (1367,)  \n",
       "                                                                      16   (1367,)  \n",
       "                                                                      4    (1367,)  \n",
       "                                                                      6    (1367,)  \n",
       "                                                                      8    (1367,)  \n",
       "                                                                 SVD  12   (1367,)  \n",
       "                                                                      16   (1367,)  \n",
       "                                                                      4    (1367,)  \n",
       "                                                                      6    (1367,)  \n",
       "                                                                      8    (1367,)  \n",
       "                               TIB         32     decomposition  LDA  12   (2549,)  \n",
       "                                                                      16   (2549,)  \n",
       "                                                                      4          -  \n",
       "                                                                      6          -  \n",
       "                                                                      8          -  \n",
       "                                                                 NMF  12   (2549,)  \n",
       "                                                                      16   (2549,)  \n",
       "                                                                      4          -  \n",
       "                                                                      6          -  \n",
       "                                                                      8          -  \n",
       "                                                                 PCA  12   (2549,)  \n",
       "                                                                      16   (2549,)  \n",
       "                                                                      4          -  \n",
       "                                                                      6          -  \n",
       "                                                                      8          -  \n",
       "                                                                 SVD  12   (2549,)  \n",
       "                                                                      16   (2549,)  \n",
       "                                                                      4          -  \n",
       "                                                                      6          -  \n",
       "                                                                      8          -  \n",
       "                               TIBC        32     decomposition  LDA  12   (3257,)  \n",
       "                                                                      16   (3257,)  \n",
       "                                                                      4          -  \n",
       "                                                                      6          -  \n",
       "                                                                      8          -  \n",
       "                                                                 NMF  12   (3257,)  \n",
       "                                                                      16   (3257,)  \n",
       "                                                                      4          -  \n",
       "                                                                      6          -  \n",
       "                                                                      8          -  \n",
       "                                                                 PCA  12   (3257,)  \n",
       "                                                                      16   (3257,)  \n",
       "                                                                      4          -  \n",
       "                                                                      6          -  \n",
       "                                                                      8          -  \n",
       "                                                                 SVD  12   (3257,)  \n",
       "                                                                      16   (3257,)  \n",
       "                                                                      4          -  \n",
       "                                                                      6          -  \n",
       "                                                                      8          -  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from src import decomposition\n",
    "from src.algo import cell2string\n",
    "\n",
    "tfidf       = '32'\n",
    "htmlfeature = ['T', 'TIB', 'TIBC']\n",
    "algo        = ['PCA', 'LDA', 'NMF', 'SVD']\n",
    "dims        = ['2', '3', '12', '16', '24', '50', '100', '150', '200', '300'] #['4', '6', '8', '12', '16']\n",
    "\n",
    "inputspace = decomposition.DecompositionFrame().sort_index().sort_index(axis=1)\n",
    "decompplan = inputspace.loc[('stackoverflow', 'lemma', 'nltk', htmlfeature, tfidf, 'decomposition', algo, dims)]\n",
    "decompplan = cell2string.file2shape(decompplan)\n",
    "decompplan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "19f63d457b074e178f696db95a4c2ec2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "FloatProgress(value=0.0, max=60.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>COMP</th>\n",
       "      <th>P</th>\n",
       "      <th>assertF</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>source</th>\n",
       "      <th>wordtype</th>\n",
       "      <th>vecimpl</th>\n",
       "      <th>htmlfeature</th>\n",
       "      <th>tf-idf</th>\n",
       "      <th>transformation</th>\n",
       "      <th>algo</th>\n",
       "      <th>dim</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"60\" valign=\"top\">stackoverflow</th>\n",
       "      <th rowspan=\"60\" valign=\"top\">lemma</th>\n",
       "      <th rowspan=\"60\" valign=\"top\">nltk</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">T</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">32</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">decomposition</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">LDA</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 1367)</td>\n",
       "      <td>(10214, 12)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 1367)</td>\n",
       "      <td>(10214, 16)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 1367)</td>\n",
       "      <td>(10214, 4)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 1367)</td>\n",
       "      <td>(10214, 6)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 1367)</td>\n",
       "      <td>(10214, 8)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">NMF</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 1367)</td>\n",
       "      <td>(10214, 12)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 1367)</td>\n",
       "      <td>(10214, 16)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 1367)</td>\n",
       "      <td>(10214, 4)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 1367)</td>\n",
       "      <td>(10214, 6)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 1367)</td>\n",
       "      <td>(10214, 8)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">PCA</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 1367)</td>\n",
       "      <td>(10214, 12)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 1367)</td>\n",
       "      <td>(10214, 16)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 1367)</td>\n",
       "      <td>(10214, 4)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 1367)</td>\n",
       "      <td>(10214, 6)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 1367)</td>\n",
       "      <td>(10214, 8)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SVD</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 1367)</td>\n",
       "      <td>(10214, 12)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 1367)</td>\n",
       "      <td>(10214, 16)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 1367)</td>\n",
       "      <td>(10214, 4)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 1367)</td>\n",
       "      <td>(10214, 6)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 1367)</td>\n",
       "      <td>(10214, 8)</td>\n",
       "      <td>(1367,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"20\" valign=\"top\">TIB</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">32</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">decomposition</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">LDA</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 2549)</td>\n",
       "      <td>(21711, 12)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 2549)</td>\n",
       "      <td>(21711, 16)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 2549)</td>\n",
       "      <td>(21711, 4)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 2549)</td>\n",
       "      <td>(21711, 6)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 2549)</td>\n",
       "      <td>(21711, 8)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">NMF</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 2549)</td>\n",
       "      <td>(21711, 12)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 2549)</td>\n",
       "      <td>(21711, 16)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 2549)</td>\n",
       "      <td>(21711, 4)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 2549)</td>\n",
       "      <td>(21711, 6)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 2549)</td>\n",
       "      <td>(21711, 8)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">PCA</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 2549)</td>\n",
       "      <td>(21711, 12)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 2549)</td>\n",
       "      <td>(21711, 16)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 2549)</td>\n",
       "      <td>(21711, 4)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 2549)</td>\n",
       "      <td>(21711, 6)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 2549)</td>\n",
       "      <td>(21711, 8)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SVD</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 2549)</td>\n",
       "      <td>(21711, 12)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 2549)</td>\n",
       "      <td>(21711, 16)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 2549)</td>\n",
       "      <td>(21711, 4)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 2549)</td>\n",
       "      <td>(21711, 6)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 2549)</td>\n",
       "      <td>(21711, 8)</td>\n",
       "      <td>(2549,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"20\" valign=\"top\">TIBC</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">32</th>\n",
       "      <th rowspan=\"20\" valign=\"top\">decomposition</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">LDA</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 3257)</td>\n",
       "      <td>(23120, 12)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 3257)</td>\n",
       "      <td>(23120, 16)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 3257)</td>\n",
       "      <td>(23120, 4)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 3257)</td>\n",
       "      <td>(23120, 6)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 3257)</td>\n",
       "      <td>(23120, 8)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">NMF</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 3257)</td>\n",
       "      <td>(23120, 12)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 3257)</td>\n",
       "      <td>(23120, 16)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 3257)</td>\n",
       "      <td>(23120, 4)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 3257)</td>\n",
       "      <td>(23120, 6)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 3257)</td>\n",
       "      <td>(23120, 8)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">PCA</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 3257)</td>\n",
       "      <td>(23120, 12)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 3257)</td>\n",
       "      <td>(23120, 16)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 3257)</td>\n",
       "      <td>(23120, 4)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 3257)</td>\n",
       "      <td>(23120, 6)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 3257)</td>\n",
       "      <td>(23120, 8)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SVD</th>\n",
       "      <th>12</th>\n",
       "      <td>(12, 3257)</td>\n",
       "      <td>(23120, 12)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>(16, 3257)</td>\n",
       "      <td>(23120, 16)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(4, 3257)</td>\n",
       "      <td>(23120, 4)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(6, 3257)</td>\n",
       "      <td>(23120, 6)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>(8, 3257)</td>\n",
       "      <td>(23120, 8)</td>\n",
       "      <td>(3257,)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                 COMP  \\\n",
       "source        wordtype vecimpl htmlfeature tf-idf transformation algo dim               \n",
       "stackoverflow lemma    nltk    T           32     decomposition  LDA  12   (12, 1367)   \n",
       "                                                                      16   (16, 1367)   \n",
       "                                                                      4     (4, 1367)   \n",
       "                                                                      6     (6, 1367)   \n",
       "                                                                      8     (8, 1367)   \n",
       "                                                                 NMF  12   (12, 1367)   \n",
       "                                                                      16   (16, 1367)   \n",
       "                                                                      4     (4, 1367)   \n",
       "                                                                      6     (6, 1367)   \n",
       "                                                                      8     (8, 1367)   \n",
       "                                                                 PCA  12   (12, 1367)   \n",
       "                                                                      16   (16, 1367)   \n",
       "                                                                      4     (4, 1367)   \n",
       "                                                                      6     (6, 1367)   \n",
       "                                                                      8     (8, 1367)   \n",
       "                                                                 SVD  12   (12, 1367)   \n",
       "                                                                      16   (16, 1367)   \n",
       "                                                                      4     (4, 1367)   \n",
       "                                                                      6     (6, 1367)   \n",
       "                                                                      8     (8, 1367)   \n",
       "                               TIB         32     decomposition  LDA  12   (12, 2549)   \n",
       "                                                                      16   (16, 2549)   \n",
       "                                                                      4     (4, 2549)   \n",
       "                                                                      6     (6, 2549)   \n",
       "                                                                      8     (8, 2549)   \n",
       "                                                                 NMF  12   (12, 2549)   \n",
       "                                                                      16   (16, 2549)   \n",
       "                                                                      4     (4, 2549)   \n",
       "                                                                      6     (6, 2549)   \n",
       "                                                                      8     (8, 2549)   \n",
       "                                                                 PCA  12   (12, 2549)   \n",
       "                                                                      16   (16, 2549)   \n",
       "                                                                      4     (4, 2549)   \n",
       "                                                                      6     (6, 2549)   \n",
       "                                                                      8     (8, 2549)   \n",
       "                                                                 SVD  12   (12, 2549)   \n",
       "                                                                      16   (16, 2549)   \n",
       "                                                                      4     (4, 2549)   \n",
       "                                                                      6     (6, 2549)   \n",
       "                                                                      8     (8, 2549)   \n",
       "                               TIBC        32     decomposition  LDA  12   (12, 3257)   \n",
       "                                                                      16   (16, 3257)   \n",
       "                                                                      4     (4, 3257)   \n",
       "                                                                      6     (6, 3257)   \n",
       "                                                                      8     (8, 3257)   \n",
       "                                                                 NMF  12   (12, 3257)   \n",
       "                                                                      16   (16, 3257)   \n",
       "                                                                      4     (4, 3257)   \n",
       "                                                                      6     (6, 3257)   \n",
       "                                                                      8     (8, 3257)   \n",
       "                                                                 PCA  12   (12, 3257)   \n",
       "                                                                      16   (16, 3257)   \n",
       "                                                                      4     (4, 3257)   \n",
       "                                                                      6     (6, 3257)   \n",
       "                                                                      8     (8, 3257)   \n",
       "                                                                 SVD  12   (12, 3257)   \n",
       "                                                                      16   (16, 3257)   \n",
       "                                                                      4     (4, 3257)   \n",
       "                                                                      6     (6, 3257)   \n",
       "                                                                      8     (8, 3257)   \n",
       "\n",
       "                                                                                     P  \\\n",
       "source        wordtype vecimpl htmlfeature tf-idf transformation algo dim                \n",
       "stackoverflow lemma    nltk    T           32     decomposition  LDA  12   (10214, 12)   \n",
       "                                                                      16   (10214, 16)   \n",
       "                                                                      4     (10214, 4)   \n",
       "                                                                      6     (10214, 6)   \n",
       "                                                                      8     (10214, 8)   \n",
       "                                                                 NMF  12   (10214, 12)   \n",
       "                                                                      16   (10214, 16)   \n",
       "                                                                      4     (10214, 4)   \n",
       "                                                                      6     (10214, 6)   \n",
       "                                                                      8     (10214, 8)   \n",
       "                                                                 PCA  12   (10214, 12)   \n",
       "                                                                      16   (10214, 16)   \n",
       "                                                                      4     (10214, 4)   \n",
       "                                                                      6     (10214, 6)   \n",
       "                                                                      8     (10214, 8)   \n",
       "                                                                 SVD  12   (10214, 12)   \n",
       "                                                                      16   (10214, 16)   \n",
       "                                                                      4     (10214, 4)   \n",
       "                                                                      6     (10214, 6)   \n",
       "                                                                      8     (10214, 8)   \n",
       "                               TIB         32     decomposition  LDA  12   (21711, 12)   \n",
       "                                                                      16   (21711, 16)   \n",
       "                                                                      4     (21711, 4)   \n",
       "                                                                      6     (21711, 6)   \n",
       "                                                                      8     (21711, 8)   \n",
       "                                                                 NMF  12   (21711, 12)   \n",
       "                                                                      16   (21711, 16)   \n",
       "                                                                      4     (21711, 4)   \n",
       "                                                                      6     (21711, 6)   \n",
       "                                                                      8     (21711, 8)   \n",
       "                                                                 PCA  12   (21711, 12)   \n",
       "                                                                      16   (21711, 16)   \n",
       "                                                                      4     (21711, 4)   \n",
       "                                                                      6     (21711, 6)   \n",
       "                                                                      8     (21711, 8)   \n",
       "                                                                 SVD  12   (21711, 12)   \n",
       "                                                                      16   (21711, 16)   \n",
       "                                                                      4     (21711, 4)   \n",
       "                                                                      6     (21711, 6)   \n",
       "                                                                      8     (21711, 8)   \n",
       "                               TIBC        32     decomposition  LDA  12   (23120, 12)   \n",
       "                                                                      16   (23120, 16)   \n",
       "                                                                      4     (23120, 4)   \n",
       "                                                                      6     (23120, 6)   \n",
       "                                                                      8     (23120, 8)   \n",
       "                                                                 NMF  12   (23120, 12)   \n",
       "                                                                      16   (23120, 16)   \n",
       "                                                                      4     (23120, 4)   \n",
       "                                                                      6     (23120, 6)   \n",
       "                                                                      8     (23120, 8)   \n",
       "                                                                 PCA  12   (23120, 12)   \n",
       "                                                                      16   (23120, 16)   \n",
       "                                                                      4     (23120, 4)   \n",
       "                                                                      6     (23120, 6)   \n",
       "                                                                      8     (23120, 8)   \n",
       "                                                                 SVD  12   (23120, 12)   \n",
       "                                                                      16   (23120, 16)   \n",
       "                                                                      4     (23120, 4)   \n",
       "                                                                      6     (23120, 6)   \n",
       "                                                                      8     (23120, 8)   \n",
       "\n",
       "                                                                           assertF  \n",
       "source        wordtype vecimpl htmlfeature tf-idf transformation algo dim           \n",
       "stackoverflow lemma    nltk    T           32     decomposition  LDA  12   (1367,)  \n",
       "                                                                      16   (1367,)  \n",
       "                                                                      4    (1367,)  \n",
       "                                                                      6    (1367,)  \n",
       "                                                                      8    (1367,)  \n",
       "                                                                 NMF  12   (1367,)  \n",
       "                                                                      16   (1367,)  \n",
       "                                                                      4    (1367,)  \n",
       "                                                                      6    (1367,)  \n",
       "                                                                      8    (1367,)  \n",
       "                                                                 PCA  12   (1367,)  \n",
       "                                                                      16   (1367,)  \n",
       "                                                                      4    (1367,)  \n",
       "                                                                      6    (1367,)  \n",
       "                                                                      8    (1367,)  \n",
       "                                                                 SVD  12   (1367,)  \n",
       "                                                                      16   (1367,)  \n",
       "                                                                      4    (1367,)  \n",
       "                                                                      6    (1367,)  \n",
       "                                                                      8    (1367,)  \n",
       "                               TIB         32     decomposition  LDA  12   (2549,)  \n",
       "                                                                      16   (2549,)  \n",
       "                                                                      4    (2549,)  \n",
       "                                                                      6    (2549,)  \n",
       "                                                                      8    (2549,)  \n",
       "                                                                 NMF  12   (2549,)  \n",
       "                                                                      16   (2549,)  \n",
       "                                                                      4    (2549,)  \n",
       "                                                                      6    (2549,)  \n",
       "                                                                      8    (2549,)  \n",
       "                                                                 PCA  12   (2549,)  \n",
       "                                                                      16   (2549,)  \n",
       "                                                                      4    (2549,)  \n",
       "                                                                      6    (2549,)  \n",
       "                                                                      8    (2549,)  \n",
       "                                                                 SVD  12   (2549,)  \n",
       "                                                                      16   (2549,)  \n",
       "                                                                      4    (2549,)  \n",
       "                                                                      6    (2549,)  \n",
       "                                                                      8    (2549,)  \n",
       "                               TIBC        32     decomposition  LDA  12   (3257,)  \n",
       "                                                                      16   (3257,)  \n",
       "                                                                      4    (3257,)  \n",
       "                                                                      6    (3257,)  \n",
       "                                                                      8    (3257,)  \n",
       "                                                                 NMF  12   (3257,)  \n",
       "                                                                      16   (3257,)  \n",
       "                                                                      4    (3257,)  \n",
       "                                                                      6    (3257,)  \n",
       "                                                                      8    (3257,)  \n",
       "                                                                 PCA  12   (3257,)  \n",
       "                                                                      16   (3257,)  \n",
       "                                                                      4    (3257,)  \n",
       "                                                                      6    (3257,)  \n",
       "                                                                      8    (3257,)  \n",
       "                                                                 SVD  12   (3257,)  \n",
       "                                                                      16   (3257,)  \n",
       "                                                                      4    (3257,)  \n",
       "                                                                      6    (3257,)  \n",
       "                                                                      8    (3257,)  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from src import decomposition\n",
    "decomposition.createDecompositions(decompplan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 2, 3, 4, 5]\n",
      "This is the format of your plot grid:\n",
      "[ (1,1) x1,y1 ]  [ (1,2) x2,y2 ]  [ (1,3) x3,y3 ]  [ (1,4) x4,y4 ]  [ (1,5) x5,y5 ]  [ (1,6) x6,y6 ]\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~MichaelGlatzhofer/24.embed\" height=\"400px\" width=\"100%\"></iframe>"
      ],
      "text/plain": [
       "<plotly.tools.PlotlyDisplay object>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from src import decomposition\n",
    "decomposition.plotComponents('stackoverflow/lemma/nltk/T/32', 'LDA', 100, [0, 6])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unsupervised Algorithms\n",
    "\n",
    "TODO: write.<br> \n",
    "applied to each composition\n",
    "\n",
    "Plot rrecision recall for each tag❌algo."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9295361cd2d640cb8a88d414e612fd81",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "FloatProgress(value=0.0, max=756.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from src import cluster\n",
    "decompositions = ['PCA', 'NMF', 'LDA', 'SVD']\n",
    "dimensions =     ['12', '16', '24', '50', '100', '150', '200']\n",
    "algos =          ['Ward', 'DBScan', 'K-Means']  # Ward K-Means GMM DBScan Affinity\n",
    "clustercount =   [20, 30, 50, 75, 100, 125, 150, 175, 200]\n",
    "cluster.cluster('stackoverflow/lemma/nltk/TIB/32/', decompositions, dimensions, algos, clustercount)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d82c88bb6e224b619815ee27f7584956",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "FloatProgress(value=0.0, max=756.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10214,)\n",
      "PCA 200 K-Means 30 f1# 0.813953488372093 2\n",
      "NMF 100 DBScan 75 f1# 0.6133333333333333 2\n",
      "LDA 150 Ward 175 f1# 0.5649717514124294 2\n",
      "SVD 100 K-Means 175 f1# 0.8068181818181819 4\n"
     ]
    }
   ],
   "source": [
    "from src import cluster\n",
    "decompositions = ['PCA', 'NMF', 'LDA', 'SVD']\n",
    "dimensions =     ['12', '16', '24', '50', '100', '150', '200']\n",
    "algos =          ['Ward', 'DBScan', 'K-Means'] # Ward K-Means GMM DBScan Affinity\n",
    "clustercount =   [20, 30, 50, 75, 100, 125, 150, 175, 200]\n",
    "cluster.clusterScore('stackoverflow/lemma/nltk/T/32/', decompositions, dimensions, algos, clustercount, 'pandas') # pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9c80bc489f034d828dad0d5afea2d2d3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "FloatProgress(value=0.0, max=4.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10214, 1367) (10214,) (1367,)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1152 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from src import cluster\n",
    "decompositions = ['PCA', 'NMF', 'LDA', 'SVD'] # PCA NMF LDA SVD FastICA FA Dict\n",
    "algos =          ['Ward', 'DBScan', 'K-Means', 'GMM']  # Ward K-Means GMM DBScan Affinity\n",
    "clustercount =   [5, 10, 15, 20, 30]\n",
    "classes =        ['python', 'pandas']\n",
    "cluster.run('stackoverflow/lemma/nltk/T/32/', decompositions, algos, 2000, 12, 25, 'python')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "find best matching cluster (maybe vary cluster count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <style  type=\"text/css\" >\n",
       "        \n",
       "        \n",
       "        </style>\n",
       "\n",
       "        <table id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33\" None>\n",
       "        \n",
       "\n",
       "        <thead>\n",
       "            \n",
       "            <tr>\n",
       "                \n",
       "                \n",
       "                <th class=\"blank level0\" >\n",
       "                  \n",
       "                \n",
       "                \n",
       "                \n",
       "                <th class=\"col_heading level0 col0\" colspan=1>\n",
       "                  A\n",
       "                \n",
       "                \n",
       "                \n",
       "                <th class=\"col_heading level0 col1\" colspan=1>\n",
       "                  B\n",
       "                \n",
       "                \n",
       "                \n",
       "                <th class=\"col_heading level0 col2\" colspan=1>\n",
       "                  C\n",
       "                \n",
       "                \n",
       "                \n",
       "                <th class=\"col_heading level0 col3\" colspan=1>\n",
       "                  D\n",
       "                \n",
       "                \n",
       "                \n",
       "                <th class=\"col_heading level0 col4\" colspan=1>\n",
       "                  E\n",
       "                \n",
       "                \n",
       "                \n",
       "                <th class=\"col_heading level0 col5\" colspan=1>\n",
       "                  F\n",
       "                \n",
       "                \n",
       "            </tr>\n",
       "            \n",
       "        </thead>\n",
       "        <tbody>\n",
       "            \n",
       "            <tr>\n",
       "                \n",
       "                \n",
       "                <th id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33\"\n",
       "                 class=\"row_heading level0 row0\" rowspan=1>\n",
       "                    0\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row0_col0\"\n",
       "                 class=\"data row0 col0\" >\n",
       "                    1\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row0_col1\"\n",
       "                 class=\"data row0 col1\" >\n",
       "                    2013-01-02 00:00:00\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row0_col2\"\n",
       "                 class=\"data row0 col2\" >\n",
       "                    1\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row0_col3\"\n",
       "                 class=\"data row0 col3\" >\n",
       "                    3\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row0_col4\"\n",
       "                 class=\"data row0 col4\" >\n",
       "                    test\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row0_col5\"\n",
       "                 class=\"data row0 col5\" >\n",
       "                    foo\n",
       "                \n",
       "                \n",
       "            </tr>\n",
       "            \n",
       "            <tr>\n",
       "                \n",
       "                \n",
       "                <th id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33\"\n",
       "                 class=\"row_heading level0 row1\" rowspan=1>\n",
       "                    1\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row1_col0\"\n",
       "                 class=\"data row1 col0\" >\n",
       "                    1\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row1_col1\"\n",
       "                 class=\"data row1 col1\" >\n",
       "                    2013-01-02 00:00:00\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row1_col2\"\n",
       "                 class=\"data row1 col2\" >\n",
       "                    1\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row1_col3\"\n",
       "                 class=\"data row1 col3\" >\n",
       "                    3\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row1_col4\"\n",
       "                 class=\"data row1 col4\" >\n",
       "                    train\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row1_col5\"\n",
       "                 class=\"data row1 col5\" >\n",
       "                    foo\n",
       "                \n",
       "                \n",
       "            </tr>\n",
       "            \n",
       "            <tr>\n",
       "                \n",
       "                \n",
       "                <th id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33\"\n",
       "                 class=\"row_heading level0 row2\" rowspan=1>\n",
       "                    2\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row2_col0\"\n",
       "                 class=\"data row2 col0\" >\n",
       "                    1\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row2_col1\"\n",
       "                 class=\"data row2 col1\" >\n",
       "                    2013-01-02 00:00:00\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row2_col2\"\n",
       "                 class=\"data row2 col2\" >\n",
       "                    1\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row2_col3\"\n",
       "                 class=\"data row2 col3\" >\n",
       "                    3\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row2_col4\"\n",
       "                 class=\"data row2 col4\" >\n",
       "                    test\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row2_col5\"\n",
       "                 class=\"data row2 col5\" >\n",
       "                    foo\n",
       "                \n",
       "                \n",
       "            </tr>\n",
       "            \n",
       "            <tr>\n",
       "                \n",
       "                \n",
       "                <th id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33\"\n",
       "                 class=\"row_heading level0 row3\" rowspan=1>\n",
       "                    3\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row3_col0\"\n",
       "                 class=\"data row3 col0\" >\n",
       "                    1\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row3_col1\"\n",
       "                 class=\"data row3 col1\" >\n",
       "                    2013-01-02 00:00:00\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row3_col2\"\n",
       "                 class=\"data row3 col2\" >\n",
       "                    1\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row3_col3\"\n",
       "                 class=\"data row3 col3\" >\n",
       "                    3\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row3_col4\"\n",
       "                 class=\"data row3 col4\" >\n",
       "                    train\n",
       "                \n",
       "                \n",
       "                \n",
       "                <td id=\"T_ff491226_5dfa_11e8_9228_7cdd902cfd33row3_col5\"\n",
       "                 class=\"data row3 col5\" >\n",
       "                    foo\n",
       "                \n",
       "                \n",
       "            </tr>\n",
       "            \n",
       "        </tbody>\n",
       "        </table>\n",
       "        "
      ],
      "text/plain": [
       "<pandas.formats.style.Styler at 0x7f71f3e81e48>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import plotly.plotly as py\n",
    "import pandas as pd\n",
    "\n",
    "df2 = pd.DataFrame({\n",
    "    'A' : 1.,\n",
    "    'B' : pd.Timestamp('20130102'),\n",
    "    'C' : pd.Series(1,index=list(range(4)), dtype='float32'),\n",
    "    'D' : np.array([3] * 4, dtype='int32'),\n",
    "    'E' : pd.Categorical([\"test\",\"train\",\"test\",\"train\"]),\n",
    "    'F' : 'foo' \n",
    "})\n",
    "\n",
    "df2.style\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hierarchical Clustering (ward)\n",
    "\n",
    "TODO: write.<br> \n",
    "for each projection (svd, pca, lda) scipy.linkage(ward) algo <br>    \n",
    "    --> for each node find decendantes, sum up raw tf, find top 3, safe tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dist/visualisations/hierarchies/LDA12-ward.d3.json\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe width=\"100%\" \n",
       "                height=\"900\"\n",
       "                frameBorder=\"0\" \n",
       "                src=\"http://localhost:3000/dist/visualisations/tree.html?f=LDA12-ward&q=python\"\n",
       "        </iframe>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from src import hierarchy\n",
    "hierarchy.run('stackoverflow/lemma/nltk/T/32', 'LDA', 12, 'python')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Install"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "#!gulp "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Traceback (most recent call last):\n",
      "  File \"/usr/bin/pip3\", line 9, in <module>\n",
      "    from pip import main\n",
      "ImportError: cannot import name 'main'\n"
     ]
    }
   ],
   "source": [
    "!pip3 install pandas\n",
    "\n",
    "import plotly\n",
    "plotly.tools.set_credentials_file(username=USER_NAME, api_key=API_KEY)"
   ]
  }
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