DR_NN.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "adde873f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "from ucimlrepo import fetch_ucirepo \n",
    "from collections import Counter\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import preprocessing\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.mixture import GaussianMixture\n",
    "from sklearn.metrics import silhouette_samples, silhouette_score\n",
    "import matplotlib.cm as cm\n",
    "from sklearn import metrics\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from scipy.spatial.distance import cdist\n",
    "import time\n",
    "import seaborn as sns\n",
    "from matplotlib.patches import Ellipse\n",
    "from kneed import KneeLocator\n",
    "import itertools\n",
    "import matplotlib as mpl\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from scipy.stats import kurtosis\n",
    "from sklearn.decomposition import FastICA\n",
    "from numpy import linalg\n",
    "from sklearn.random_projection import GaussianRandomProjection\n",
    "from sklearn import metrics\n",
    "from itertools import product\n",
    "from collections import defaultdict\n",
    "from sklearn.manifold import LocallyLinearEmbedding\n",
    "from imblearn.pipeline import Pipeline\n",
    "from imblearn.over_sampling import SMOTE\n",
    "from sklearn.model_selection import learning_curve\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import classification_report, confusion_matrix\n",
    "from matplotlib import rcParams\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "83bbec84",
   "metadata": {},
   "outputs": [],
   "source": [
    "RANDOM_STATE = 101\n",
    "seeds = [1, 10, 25, 50, 101]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9b0fa8ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Breast Cancer Data\n",
    "# fetch dataset \n",
    "bc_df = fetch_ucirepo(id=17) \n",
    "  \n",
    "# data (as pandas dataframes) \n",
    "X = bc_df.data.features \n",
    "y = bc_df.data.targets "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "aefba425",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split into training and testing sets. Don't use test set until the very end\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.2, random_state=RANDOM_STATE, stratify = y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4640c72",
   "metadata": {},
   "source": [
    "## ICA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6ede27ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "                (&#x27;model&#x27;,\n",
       "                 MLPClassifier(alpha=0.1, early_stopping=True,\n",
       "                               hidden_layer_sizes=(100, 100, 100),\n",
       "                               max_iter=2000, random_state=101))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Pipeline</label><div class=\"sk-toggleable__content\"><pre>Pipeline(steps=[(&#x27;norm&#x27;, MinMaxScaler()), (&#x27;sm&#x27;, SMOTE(random_state=101)),\n",
       "                (&#x27;model&#x27;,\n",
       "                 MLPClassifier(alpha=0.1, early_stopping=True,\n",
       "                               hidden_layer_sizes=(100, 100, 100),\n",
       "                               max_iter=2000, random_state=101))])</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">MinMaxScaler</label><div class=\"sk-toggleable__content\"><pre>MinMaxScaler()</pre></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SMOTE</label><div class=\"sk-toggleable__content\"><pre>SMOTE(random_state=101)</pre></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">MLPClassifier</label><div class=\"sk-toggleable__content\"><pre>MLPClassifier(alpha=0.1, early_stopping=True,\n",
       "              hidden_layer_sizes=(100, 100, 100), max_iter=2000,\n",
       "              random_state=101)</pre></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('norm', MinMaxScaler()), ('sm', SMOTE(random_state=101)),\n",
       "                ('model',\n",
       "                 MLPClassifier(alpha=0.1, early_stopping=True,\n",
       "                               hidden_layer_sizes=(100, 100, 100),\n",
       "                               max_iter=2000, random_state=101))])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf = MLPClassifier(random_state=RANDOM_STATE, max_iter=2000, early_stopping=True, alpha=.1, hidden_layer_sizes=(100,100,100))\n",
    "sm = SMOTE(random_state=RANDOM_STATE)\n",
    "norm = MinMaxScaler()\n",
    "pipeline = Pipeline([('norm', norm), ('sm', sm), ('model', clf)])\n",
    "pipeline.fit(X_train, y_train.values.ravel())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "196a0a8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = pipeline.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a9709a59",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.93      0.96      0.95        72\n",
      "           M       0.93      0.88      0.90        42\n",
      "\n",
      "    accuracy                           0.93       114\n",
      "   macro avg       0.93      0.92      0.92       114\n",
      "weighted avg       0.93      0.93      0.93       114\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# print classification report \n",
    "print(classification_report(y_test, y_pred)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a58a7023",
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = MLPClassifier(random_state=RANDOM_STATE, max_iter=2000, early_stopping=True, alpha=.1, hidden_layer_sizes=(100,100,100))\n",
    "sm = SMOTE(random_state=RANDOM_STATE)\n",
    "norm = MinMaxScaler()\n",
    "pipeline = Pipeline([('norm', norm), ('sm', sm), ('model', clf)])\n",
    "pipeline.fit(X_train, y_train.values.ravel())\n",
    "train_sizes, train_scores, validation_scores = learning_curve(\n",
    "estimator = pipeline,\n",
    "X = X_train,\n",
    "y = y_train.values.ravel(), cv = 5,\n",
    "scoring = 'f1_macro',\n",
    "random_state=RANDOM_STATE)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a4b94d2",
   "metadata": {},
   "source": [
    "### Final Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8a00d073",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training time: 0.36211705207824707\n"
     ]
    }
   ],
   "source": [
    "clf = MLPClassifier(random_state=RANDOM_STATE, max_iter=2000, early_stopping=True, alpha=.5, hidden_layer_sizes=(150,150,))\n",
    "sm = SMOTE(random_state=RANDOM_STATE)\n",
    "norm = MinMaxScaler()\n",
    "ica = FastICA(n_components=27, random_state=RANDOM_STATE)\n",
    "ica_pipeline = Pipeline([('norm', norm), ('ica', ica), ('sm', sm), ('model', clf)])\n",
    "t0 = time.time()\n",
    "ica_pipeline.fit(X_train, y_train.values.ravel())\n",
    "print(\"Training time:\", time.time()-t0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "76a7153e",
   "metadata": {},
   "outputs": [],
   "source": [
    "ica_y_pred = ica_pipeline.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1946e1dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.96      0.96      0.96        72\n",
      "           M       0.93      0.93      0.93        42\n",
      "\n",
      "    accuracy                           0.95       114\n",
      "   macro avg       0.94      0.94      0.94       114\n",
      "weighted avg       0.95      0.95      0.95       114\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# print classification report \n",
    "print(classification_report(y_test, ica_y_pred)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7ee0549b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "clf = MLPClassifier(random_state=RANDOM_STATE, max_iter=2000, early_stopping=True, alpha=.5, hidden_layer_sizes=(150,150,))\n",
    "sm = SMOTE(random_state=RANDOM_STATE)\n",
    "norm = MinMaxScaler()\n",
    "ica = FastICA(n_components=27, random_state=RANDOM_STATE, max_iter=500)\n",
    "ica_pipeline = Pipeline([('norm', norm), ('ica', ica), ('sm', sm), ('model', clf)])\n",
    "ica_pipeline.fit(X_train, y_train.values.ravel())\n",
    "ica_train_sizes, ica_train_scores, ica_validation_scores = learning_curve(\n",
    "estimator = ica_pipeline,\n",
    "X = X_train,\n",
    "y = y_train.values.ravel(), cv = 5,\n",
    "scoring = 'f1_macro',\n",
    "random_state=RANDOM_STATE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c10b0594",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(18, 6))\n",
    "rcParams['font.weight'] = 'bold'\n",
    "ica_train_mean = ica_train_scores.mean(axis=1)\n",
    "ica_validation_mean = ica_validation_scores.mean(axis=1)\n",
    "train_mean = train_scores.mean(axis=1)\n",
    "validation_mean = validation_scores.mean(axis=1)\n",
    "\n",
    "ax1.plot(pipeline['model'].loss_curve_, label='a1 training')\n",
    "ax1.plot(pipeline['model'].validation_scores_, label='a1 validation')\n",
    "ax1.plot(ica_pipeline['model'].loss_curve_, label='ica training')\n",
    "ax1.plot(ica_pipeline['model'].validation_scores_, label='ica validation')\n",
    "ax1.legend(loc=\"best\", prop = { 'weight':'bold'})\n",
    "ax1.set_xlabel('Epochs', weight='bold')\n",
    "ax1.set_title('Epoch Learning Curve', weight='bold')\n",
    "ax1.set_ylabel('Loss', weight='bold')\n",
    "ax1.grid()\n",
    "\n",
    "ax2.plot(train_sizes, train_mean, label=\"a1 training\")\n",
    "ax2.plot(train_sizes, validation_mean, label=\"a1 validation\")\n",
    "ax2.plot(ica_train_sizes, ica_train_mean, label=\"ica training\")\n",
    "ax2.plot(ica_train_sizes, ica_validation_mean, label=\"ica validation\")\n",
    "\n",
    "ax2.set_title(\"Learning Curve\", weight='bold')\n",
    "ax2.set_xlabel(\"Training Set Size\", weight='bold')\n",
    "ax2.set_ylabel(\"f1 score\", weight='bold')\n",
    "ax2.legend(loc=\"best\", prop = { 'weight':'bold'})\n",
    "ax2.grid()\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'plots/dim_red_nn/bc_ica_learning.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21fc5054",
   "metadata": {},
   "source": [
    "### Validation Curves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e0be908c",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import validation_curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ff9398c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = MLPClassifier(random_state=RANDOM_STATE, max_iter=2000, early_stopping=True)\n",
    "sm = SMOTE(random_state=RANDOM_STATE)\n",
    "norm = MinMaxScaler()\n",
    "ica = FastICA(n_components=27, random_state=RANDOM_STATE, max_iter=500)\n",
    "ica_pipeline = Pipeline([('norm', norm), ('ica', ica), ('sm', sm), ('model', clf)])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c964696",
   "metadata": {},
   "source": [
    "#### Width"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "52db6957",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "width_parameter_range = [(5,), (10,), (20,), (50,), (100,), (150,), (200,), (250,), (300,)]\n",
    "width_train_score, width_test_score = validation_curve(ica_pipeline, X_train, y_train.values.ravel(),\n",
    "                                           param_name=\"model__hidden_layer_sizes\",\n",
    "                                           param_range=width_parameter_range,\n",
    "                                           cv=5, scoring=\"f1_macro\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f30f74b",
   "metadata": {},
   "source": [
    "#### Depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "1091cf8b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "depth_parameter_range = [(150,), (150,150), (150,150,150), (150,150,150,150), (150,150,150,150,150)]\n",
    "    # (5,), (5,5), (5,5,5), (5,5,5,5), (5,5,5,5,5), (5,5,5,5,5,5)]\n",
    "                   # , (10,), (10,10), (10,10,10), (10,10,10,10)]\n",
    "depth_train_score, depth_test_score = validation_curve(ica_pipeline, X_train, y_train.values.ravel(),\n",
    "                                           param_name=\"model__hidden_layer_sizes\",\n",
    "                                           param_range=depth_parameter_range,\n",
    "                                           cv=5, scoring=\"f1_macro\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4f939fc",
   "metadata": {},
   "source": [
    "#### Alpha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "023f349b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/VivianNTran/anaconda3/envs/ML_A3_env/lib/python3.11/site-packages/sklearn/decomposition/_fastica.py:128: ConvergenceWarning: FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "clf = MLPClassifier(random_state=RANDOM_STATE, max_iter=2000, early_stopping=True, hidden_layer_sizes=(150,))\n",
    "sm = SMOTE(random_state=RANDOM_STATE)\n",
    "norm = MinMaxScaler()\n",
    "ica = FastICA(n_components=27, random_state=RANDOM_STATE, max_iter=500)\n",
    "ica_pipeline = Pipeline([('norm', norm), ('ica', ica), ('sm', sm), ('model', clf)])\n",
    "alpha_parameter_range = [0.0001, 0.01, 0.05, 0.1, 0.5, 0.75, 1]\n",
    "alpha_train_score, alpha_test_score = validation_curve(ica_pipeline, X_train, y_train.values.ravel(),\n",
    "                                           param_name=\"model__alpha\",\n",
    "                                           param_range=alpha_parameter_range,\n",
    "                                           cv=5, scoring=\"f1_macro\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4bcc4d70",
   "metadata": {},
   "source": [
    "### Cumulative Validation Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "61178a0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2200x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax1, ax2, ax3)) = plt.subplots(1, 3, figsize=(22, 6))\n",
    "rcParams['font.weight'] = 'bold'\n",
    "\n",
    "# Width\n",
    "# Calculating mean and standard deviation of training score\n",
    "width_mean_train_score = np.mean(width_train_score, axis=1)\n",
    "width_std_train_score = np.std(width_train_score, axis=1)\n",
    " \n",
    "# Calculating mean and standard deviation of testing score\n",
    "width_mean_test_score = np.mean(width_test_score, axis=1)\n",
    "width_std_test_score = np.std(width_test_score, axis=1)\n",
    "\n",
    "width_parameter_range = [5, 10, 20, 50, 100, 150, 200, 250, 300]\n",
    "# Plot mean accuracy scores for training and testing scores\n",
    "ax1.plot(width_parameter_range, width_mean_train_score,\n",
    "         label=\"training\", color='b')\n",
    "ax1.plot(width_parameter_range, width_mean_test_score,\n",
    "         label=\"validation\", color='g')\n",
    " \n",
    "# Creating the plot\n",
    "ax1.set_title(\"Layer Width Validation Curve\", weight='bold')\n",
    "ax1.set_xlabel(\"Layer Width\", weight='bold')\n",
    "ax1.set_ylabel(\"f1 score\", weight='bold')\n",
    "ax1.legend(loc='best', prop = { 'weight':'bold'})\n",
    "ax1.grid()\n",
    "\n",
    "# Depth\n",
    "# Calculating mean and standard deviation of training score\n",
    "depth_mean_train_score = np.mean(depth_train_score, axis=1)\n",
    "depth_std_train_score = np.std(depth_train_score, axis=1)\n",
    " \n",
    "# Calculating mean and standard deviation of testing score\n",
    "depth_mean_test_score = np.mean(depth_test_score, axis=1)\n",
    "depth_std_test_score = np.std(depth_test_score, axis=1)\n",
    "\n",
    "depth_parameter_range = [1, 2, 3, 4, 5]\n",
    "# Plot mean accuracy scores for training and testing scores\n",
    "ax2.plot(depth_parameter_range, depth_mean_train_score,\n",
    "         label=\"training\", color='b')\n",
    "ax2.plot(depth_parameter_range, depth_mean_test_score,\n",
    "         label=\"validation\", color='g')\n",
    " \n",
    "# Creating the plot\n",
    "ax2.set_title(\"Layer Depths Validation Curve\", weight='bold')\n",
    "ax2.set_xlabel(\"Depth of Layers\", weight='bold')\n",
    "ax2.set_ylabel(\"f1 score\", weight='bold')\n",
    "ax2.legend(loc='best', prop = { 'weight':'bold'})\n",
    "ax2.grid()\n",
    "\n",
    "# Alpha\n",
    "# Calculating mean and standard deviation of training score\n",
    "alpha_mean_train_score = np.mean(alpha_train_score, axis=1)\n",
    "alpha_std_train_score = np.std(alpha_train_score, axis=1)\n",
    " \n",
    "# Calculating mean and standard deviation of testing score\n",
    "alpha_mean_test_score = np.mean(alpha_test_score, axis=1)\n",
    "alpha_std_test_score = np.std(alpha_test_score, axis=1)\n",
    "\n",
    "# Plot mean accuracy scores for training and testing scores\n",
    "ax3.plot(alpha_parameter_range, alpha_mean_train_score,\n",
    "         label=\"training\", color='b')\n",
    "ax3.plot(alpha_parameter_range, alpha_mean_test_score,\n",
    "         label=\"validation\", color='g')\n",
    " \n",
    "# Creating the plot\n",
    "ax3.set_title(\"Alpha Validation Curve\", weight='bold')\n",
    "ax3.set_xlabel(\"Alpha\", weight='bold')\n",
    "ax3.set_ylabel(\"f1 score\", weight='bold')\n",
    "ax3.legend(loc='best', prop = { 'weight':'bold'})\n",
    "ax3.grid()\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'plots/dim_red_nn/bc_ica_validation.png', dpi=300)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "340deac1",
   "metadata": {},
   "source": [
    "## Manifold Learning: LLE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "df9e4139",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {color: black;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;norm&#x27;, MinMaxScaler()), (&#x27;sm&#x27;, SMOTE(random_state=101)),\n",
       "                (&#x27;model&#x27;,\n",
       "                 MLPClassifier(alpha=0.1, early_stopping=True,\n",
       "                               hidden_layer_sizes=(100, 100, 100),\n",
       "                               max_iter=2000, random_state=101))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Pipeline</label><div class=\"sk-toggleable__content\"><pre>Pipeline(steps=[(&#x27;norm&#x27;, MinMaxScaler()), (&#x27;sm&#x27;, SMOTE(random_state=101)),\n",
       "                (&#x27;model&#x27;,\n",
       "                 MLPClassifier(alpha=0.1, early_stopping=True,\n",
       "                               hidden_layer_sizes=(100, 100, 100),\n",
       "                               max_iter=2000, random_state=101))])</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">MinMaxScaler</label><div class=\"sk-toggleable__content\"><pre>MinMaxScaler()</pre></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SMOTE</label><div class=\"sk-toggleable__content\"><pre>SMOTE(random_state=101)</pre></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">MLPClassifier</label><div class=\"sk-toggleable__content\"><pre>MLPClassifier(alpha=0.1, early_stopping=True,\n",
       "              hidden_layer_sizes=(100, 100, 100), max_iter=2000,\n",
       "              random_state=101)</pre></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('norm', MinMaxScaler()), ('sm', SMOTE(random_state=101)),\n",
       "                ('model',\n",
       "                 MLPClassifier(alpha=0.1, early_stopping=True,\n",
       "                               hidden_layer_sizes=(100, 100, 100),\n",
       "                               max_iter=2000, random_state=101))])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf = MLPClassifier(random_state=RANDOM_STATE, max_iter=2000, early_stopping=True, alpha=.1, hidden_layer_sizes=(100,100,100))\n",
    "sm = SMOTE(random_state=RANDOM_STATE)\n",
    "norm = MinMaxScaler()\n",
    "pipeline = Pipeline([('norm', norm), ('sm', sm), ('model', clf)])\n",
    "pipeline.fit(X_train, y_train.values.ravel())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "35afe873",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = pipeline.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6e1b3ad4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.93      0.96      0.95        72\n",
      "           M       0.93      0.88      0.90        42\n",
      "\n",
      "    accuracy                           0.93       114\n",
      "   macro avg       0.93      0.92      0.92       114\n",
      "weighted avg       0.93      0.93      0.93       114\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# print classification report \n",
    "print(classification_report(y_test, y_pred)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ec9ae79c",
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = MLPClassifier(random_state=RANDOM_STATE, max_iter=2000, early_stopping=True, alpha=.1, hidden_layer_sizes=(100,100,100))\n",
    "sm = SMOTE(random_state=RANDOM_STATE)\n",
    "norm = MinMaxScaler()\n",
    "pipeline = Pipeline([('norm', norm), ('sm', sm), ('model', clf)])\n",
    "pipeline.fit(X_train, y_train.values.ravel())\n",
    "train_sizes, train_scores, validation_scores = learning_curve(\n",
    "estimator = pipeline,\n",
    "X = X_train,\n",
    "y = y_train.values.ravel(), cv = 5,\n",
    "scoring = 'f1_macro',\n",
    "random_state=RANDOM_STATE)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21f574a9",
   "metadata": {},
   "source": [
    "### Final Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "cf897b09",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training time: 0.26589512825012207\n"
     ]
    }
   ],
   "source": [
    "clf = MLPClassifier(random_state=RANDOM_STATE, max_iter=2000, early_stopping=True, alpha=0, hidden_layer_sizes=(100,100,100,100,))\n",
    "sm = SMOTE(random_state=RANDOM_STATE)\n",
    "norm = MinMaxScaler()\n",
    "lle = LocallyLinearEmbedding(n_neighbors=10, n_components=4, random_state=RANDOM_STATE, n_jobs=-1)\n",
    "lle_pipeline = Pipeline([('norm', norm), ('lle', lle), ('sm', sm), ('model', clf)])\n",
    "t0 = time.time()\n",
    "lle_pipeline.fit(X_train, y_train.values.ravel())\n",
    "print(\"Training time:\", time.time()-t0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b9665d48",
   "metadata": {},
   "outputs": [],
   "source": [
    "lle_y_pred = lle_pipeline.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c375c1cc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.93      0.93      0.93        72\n",
      "           M       0.88      0.88      0.88        42\n",
      "\n",
      "    accuracy                           0.91       114\n",
      "   macro avg       0.91      0.91      0.91       114\n",
      "weighted avg       0.91      0.91      0.91       114\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# print classification report \n",
    "print(classification_report(y_test, lle_y_pred)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "51bdb407",
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = MLPClassifier(random_state=RANDOM_STATE, max_iter=2000, early_stopping=True, alpha=0, hidden_layer_sizes=(100,100,100,100,))\n",
    "sm = SMOTE(random_state=RANDOM_STATE)\n",
    "norm = MinMaxScaler()\n",
    "lle = LocallyLinearEmbedding(n_neighbors=10, n_components=4, random_state=RANDOM_STATE, n_jobs=-1)\n",
    "lle_pipeline = Pipeline([('norm', norm), ('lle', lle), ('sm', sm), ('model', clf)])\n",
    "lle_pipeline.fit(X_train, y_train.values.ravel())\n",
    "lle_train_sizes, lle_train_scores, lle_validation_scores = learning_curve(\n",
    "estimator = lle_pipeline,\n",
    "X = X_train,\n",
    "y = y_train.values.ravel(), cv = 5,\n",
    "scoring = 'f1_macro',\n",
    "random_state=RANDOM_STATE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e972ef5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(18, 6))\n",
    "rcParams['font.weight'] = 'bold'\n",
    "lle_train_mean = lle_train_scores.mean(axis=1)\n",
    "lle_validation_mean = lle_validation_scores.mean(axis=1)\n",
    "train_mean = train_scores.mean(axis=1)\n",
    "validation_mean = validation_scores.mean(axis=1)\n",
    "\n",
    "ax1.plot(pipeline['model'].loss_curve_, label='a1 training')\n",
    "ax1.plot(pipeline['model'].validation_scores_, label='a1 validation')\n",
    "ax1.plot(lle_pipeline['model'].loss_curve_, label='training')\n",
    "ax1.plot(lle_pipeline['model'].validation_scores_, label='validation')\n",
    "ax1.legend(loc=\"best\", prop = { 'weight':'bold'})\n",
    "ax1.set_xlabel('Epochs', weight='bold')\n",
    "ax1.set_title('LLE Epoch Learning Curve', weight='bold')\n",
    "ax1.set_ylabel('Loss', weight='bold')\n",
    "ax1.grid()\n",
    "\n",
    "ax2.plot(train_sizes, train_mean, label=\"a1 training\")\n",
    "ax2.plot(train_sizes, validation_mean, label=\"a1 validation\")\n",
    "ax2.plot(lle_train_sizes, lle_train_mean, label=\"train\")\n",
    "ax2.plot(lle_train_sizes, lle_validation_mean, label=\"validation\")\n",
    "\n",
    "ax2.set_title(\"LLE Learning Curve\", weight='bold')\n",
    "ax2.set_xlabel(\"Training Set Size\", weight='bold')\n",
    "ax2.set_ylabel(\"f1 score\", weight='bold')\n",
    "ax2.legend(loc=\"best\", prop = { 'weight':'bold'})\n",
    "ax2.grid()\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'plots/dim_red_nn/bc_lle_learning.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d0e18cb",
   "metadata": {},
   "source": [
    "### Validation Curves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "97ecfcbd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import validation_curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "35673ca7",
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = MLPClassifier(random_state=RANDOM_STATE, max_iter=2000, early_stopping=True)\n",
    "sm = SMOTE(random_state=RANDOM_STATE)\n",
    "norm = MinMaxScaler()\n",
    "lle = LocallyLinearEmbedding(n_neighbors=10, n_components=4, random_state=RANDOM_STATE, n_jobs=-1)\n",
    "lle_pipeline = Pipeline([('norm', norm), ('lle', lle), ('sm', sm), ('model', clf)])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa9197eb",
   "metadata": {},
   "source": [
    "#### Width"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "0a0bc77e",
   "metadata": {},
   "outputs": [],
   "source": [
    "width_parameter_range = [(5,), (10,), (20,), (50,), (100,), (150,), (200,), (250,), (300,)]\n",
    "width_train_score, width_test_score = validation_curve(lle_pipeline, X_train, y_train.values.ravel(),\n",
    "                                           param_name=\"model__hidden_layer_sizes\",\n",
    "                                           param_range=width_parameter_range,\n",
    "                                           cv=5, scoring=\"f1_macro\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0f34b1e",
   "metadata": {},
   "source": [
    "#### Depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b5978556",
   "metadata": {},
   "outputs": [],
   "source": [
    "depth_parameter_range = [(100,), (100,100), (100,100,100), (100,100,100,100), (100,100,100,100,100)]\n",
    "    # (5,), (5,5), (5,5,5), (5,5,5,5), (5,5,5,5,5), (5,5,5,5,5,5)]\n",
    "                   # , (10,), (10,10), (10,10,10), (10,10,10,10)]\n",
    "depth_train_score, depth_test_score = validation_curve(lle_pipeline, X_train, y_train.values.ravel(),\n",
    "                                           param_name=\"model__hidden_layer_sizes\",\n",
    "                                           param_range=depth_parameter_range,\n",
    "                                           cv=5, scoring=\"f1_macro\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0061b2c4",
   "metadata": {},
   "source": [
    "#### Alpha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "43ec64c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = MLPClassifier(random_state=RANDOM_STATE, max_iter=2000, early_stopping=True, hidden_layer_sizes=(100,100,100,100,))\n",
    "sm = SMOTE(random_state=RANDOM_STATE)\n",
    "norm = MinMaxScaler()\n",
    "lle = LocallyLinearEmbedding(n_neighbors=10, n_components=4, random_state=RANDOM_STATE, n_jobs=-1)\n",
    "lle_pipeline = Pipeline([('norm', norm), ('lle', lle), ('sm', sm), ('model', clf)])\n",
    "alpha_parameter_range = [0.0001, 0.01, 0.05, 0.1, 0.5, 0.75, 1]\n",
    "alpha_train_score, alpha_test_score = validation_curve(lle_pipeline, X_train, y_train.values.ravel(),\n",
    "                                           param_name=\"model__alpha\",\n",
    "                                           param_range=alpha_parameter_range,\n",
    "                                           cv=5, scoring=\"f1_macro\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "373f56f0",
   "metadata": {},
   "source": [
    "### Cumulative Validation Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "d9aef291",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2200x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax1, ax2, ax3)) = plt.subplots(1, 3, figsize=(22, 6))\n",
    "rcParams['font.weight'] = 'bold'\n",
    "\n",
    "# Width\n",
    "# Calculating mean and standard deviation of training score\n",
    "width_mean_train_score = np.mean(width_train_score, axis=1)\n",
    "width_std_train_score = np.std(width_train_score, axis=1)\n",
    " \n",
    "# Calculating mean and standard deviation of testing score\n",
    "width_mean_test_score = np.mean(width_test_score, axis=1)\n",
    "width_std_test_score = np.std(width_test_score, axis=1)\n",
    "\n",
    "width_parameter_range = [5, 10, 20, 50, 100, 150, 200, 250, 300]\n",
    "# Plot mean accuracy scores for training and testing scores\n",
    "ax1.plot(width_parameter_range, width_mean_train_score,\n",
    "         label=\"training\", color='b')\n",
    "ax1.plot(width_parameter_range, width_mean_test_score,\n",
    "         label=\"validation\", color='g')\n",
    " \n",
    "# Creating the plot\n",
    "ax1.set_title(\"Layer Width Validation Curve\", weight='bold')\n",
    "ax1.set_xlabel(\"Layer Width\", weight='bold')\n",
    "ax1.set_ylabel(\"f1 score\", weight='bold')\n",
    "ax1.legend(loc='best', prop = { 'weight':'bold'})\n",
    "ax1.grid()\n",
    "\n",
    "# Depth\n",
    "# Calculating mean and standard deviation of training score\n",
    "depth_mean_train_score = np.mean(depth_train_score, axis=1)\n",
    "depth_std_train_score = np.std(depth_train_score, axis=1)\n",
    " \n",
    "# Calculating mean and standard deviation of testing score\n",
    "depth_mean_test_score = np.mean(depth_test_score, axis=1)\n",
    "depth_std_test_score = np.std(depth_test_score, axis=1)\n",
    "\n",
    "depth_parameter_range = [1, 2, 3, 4, 5]\n",
    "# Plot mean accuracy scores for training and testing scores\n",
    "ax2.plot(depth_parameter_range, depth_mean_train_score,\n",
    "         label=\"training\", color='b')\n",
    "ax2.plot(depth_parameter_range, depth_mean_test_score,\n",
    "         label=\"validation\", color='g')\n",
    " \n",
    "# Creating the plot\n",
    "ax2.set_title(\"Layer Depths Validation Curve\", weight='bold')\n",
    "ax2.set_xlabel(\"Depth of Layers\", weight='bold')\n",
    "ax2.set_ylabel(\"f1 score\", weight='bold')\n",
    "ax2.legend(loc='best', prop = { 'weight':'bold'})\n",
    "ax2.grid()\n",
    "\n",
    "# Alpha\n",
    "# Calculating mean and standard deviation of training score\n",
    "alpha_mean_train_score = np.mean(alpha_train_score, axis=1)\n",
    "alpha_std_train_score = np.std(alpha_train_score, axis=1)\n",
    " \n",
    "# Calculating mean and standard deviation of testing score\n",
    "alpha_mean_test_score = np.mean(alpha_test_score, axis=1)\n",
    "alpha_std_test_score = np.std(alpha_test_score, axis=1)\n",
    "\n",
    "# Plot mean accuracy scores for training and testing scores\n",
    "ax3.plot(alpha_parameter_range, alpha_mean_train_score,\n",
    "         label=\"training\", color='b')\n",
    "ax3.plot(alpha_parameter_range, alpha_mean_test_score,\n",
    "         label=\"validation\", color='g')\n",
    " \n",
    "# Creating the plot\n",
    "ax3.set_title(\"Alpha Validation Curve\", weight='bold')\n",
    "ax3.set_xlabel(\"Alpha\", weight='bold')\n",
    "ax3.set_ylabel(\"f1 score\", weight='bold')\n",
    "ax3.legend(loc='best', prop = { 'weight':'bold'})\n",
    "ax3.grid()\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'plots/dim_red_nn/bc_lle_validation.png', dpi=300)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b1ad445",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}