ENH Plot predicted-vs-actual

Author: luispedro

ch07/figure4.py

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+# This code is supporting material for the book
+# Building Machine Learning Systems with Python
+# by Willi Richert and Luis Pedro Coelho
+# published by PACKT Publishing
+#
+# It is made available under the MIT License
+
+
+# This script plots prediction-vs-actual on training set for the Boston dataset
+# using OLS regression
+
+from sklearn.linear_model import LinearRegression
+from sklearn.datasets import load_boston
+import pylab as plt
+
+boston = load_boston()
+
+x = boston.data
+y = boston.target
+
+lr = LinearRegression()
+lr.fit(x, y)
+p = lr.predict(x)
+plt.scatter(p, y)
+plt.xlabel('Predicted price')
+plt.ylabel('Actual price')
+plt.plot([y.min(), y.max()], [y.min(), y.max()])
+
+plt.savefig('Figure4.png', dpi=150)