ch10 up

pursuit-of-42 · Oct 6, 2015 · b123db9 · b123db9
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diff --git a/README.md b/README.md
@@ -41,7 +41,7 @@ Excerpts from the [Foreword](./docs/foreword_ro.pdf) and [Preface](./docs/prefac
 7. Combining Different Models for Ensemble Learning [[dir](./code/ch07)] [[ipynb](./code/ch07/ch07.ipynb)] [[nbviewer](http://nbviewer.ipython.org/github/rasbt/python-machine-learning-book/blob/master/code/ch07/ch07.ipynb)]
 8. Applying Machine Learning to Sentiment Analysis [[dir](./code/ch08)] [[ipynb](./code/ch08/ch08.ipynb)] [[nbviewer](http://nbviewer.ipython.org/github/rasbt/python-machine-learning-book/blob/master/code/ch08/ch08.ipynb)]
 9. Embedding a Machine Learning Model into a Web Application [[dir](./code/ch09)] [[ipynb](./code/ch09/ch09.ipynb)] [[nbviewer](http://nbviewer.ipython.org/github/rasbt/python-machine-learning-book/blob/master/code/ch09/ch09.ipynb)]
-10. Predicting Continuous Target Variables with Regression Analysis
+10. Predicting Continuous Target Variables with Regression Analysis [[dir](./code/ch10)] [[ipynb](./code/ch10/ch10.ipynb)] [[nbviewer](http://nbviewer.ipython.org/github/rasbt/python-machine-learning-book/blob/master/code/ch10/ch10.ipynb)]
 11. Working with Unlabeled Data – Clustering Analysis
 12. Training Artificial Neural Networks for Image Recognition
 13. Parallelizing Neural Network Training via Theano

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diff --git a/code/datasets/README.md b/code/datasets/README.md
@@ -19,6 +19,11 @@ Sebastian Raschka, 2015
 
 ### movie
 
-- used in chapter 8
+- used in chapter 8, 9
 - movie dataset converted into a 2-column CSV format: The first column (`review`) contains the text, and the second column (`sentiment`) denotes the polarity, where 0=negative and 1=positive. The first 25,000 are the training samples and the remaining 25,000 rows are the test samples from the "Large Movie Review Dataset v1.0," respectively.
-- source: [http://ai.stanford.edu/~amaas/data/sentiment/](http://ai.stanford.edu/~amaas/data/sentiment/)
+- source: [http://ai.stanford.edu/~amaas/data/sentiment/](http://ai.stanford.edu/~amaas/data/sentiment/)
+
+### housing
+
+- used in chapter 10
+- source: [https://archive.ics.uci.edu/ml/datasets/Housing](https://archive.ics.uci.edu/ml/datasets/Housing)
diff --git a/code/datasets/housing/housing.data b/code/datasets/housing/housing.data
diff --git a/code/datasets/housing/housing.names.txt b/code/datasets/housing/housing.names.txt
@@ -0,0 +1,52 @@
+1. Title: Boston Housing Data
+
+2. Sources:
+   (a) Origin:  This dataset was taken from the StatLib library which is
+                maintained at Carnegie Mellon University.
+   (b) Creator:  Harrison, D. and Rubinfeld, D.L. 'Hedonic prices and the 
+                 demand for clean air', J. Environ. Economics & Management,
+                 vol.5, 81-102, 1978.
+   (c) Date: July 7, 1993
+
+3. Past Usage:
+   -   Used in Belsley, Kuh & Welsch, 'Regression diagnostics ...', Wiley, 
+       1980.   N.B. Various transformations are used in the table on
+       pages 244-261.
+    -  Quinlan,R. (1993). Combining Instance-Based and Model-Based Learning.
+       In Proceedings on the Tenth International Conference of Machine 
+       Learning, 236-243, University of Massachusetts, Amherst. Morgan
+       Kaufmann.
+
+4. Relevant Information:
+
+   Concerns housing values in suburbs of Boston.
+
+5. Number of Instances: 506
+
+6. Number of Attributes: 13 continuous attributes (including "class"
+                         attribute "MEDV"), 1 binary-valued attribute.
+
+7. Attribute Information:
+
+    1. CRIM      per capita crime rate by town
+    2. ZN        proportion of residential land zoned for lots over 
+                 25,000 sq.ft.
+    3. INDUS     proportion of non-retail business acres per town
+    4. CHAS      Charles River dummy variable (= 1 if tract bounds 
+                 river; 0 otherwise)
+    5. NOX       nitric oxides concentration (parts per 10 million)
+    6. RM        average number of rooms per dwelling
+    7. AGE       proportion of owner-occupied units built prior to 1940
+    8. DIS       weighted distances to five Boston employment centres
+    9. RAD       index of accessibility to radial highways
+    10. TAX      full-value property-tax rate per $10,000
+    11. PTRATIO  pupil-teacher ratio by town
+    12. B        1000(Bk - 0.63)^2 where Bk is the proportion of blacks 
+                 by town
+    13. LSTAT    % lower status of the population
+    14. MEDV     Median value of owner-occupied homes in $1000's
+
+8. Missing Attribute Values:  None.
+
+
+