Create logregwine.py

logregwine.py

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+# Import necessary modules
+from sklearn import linear_model
+from sklearn.cross_validation import train_test_split
+
+# Load data
+df = pd.read_csv('http://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv ' , sep = ';')
+X = df.drop('quality' , 1).values #drop target variable
+y1 = df['quality'].values
+y = y1 <= 5 # is the rating <= 5?
+
+# plot histograms of original target variable
+# and aggregated target variable
+plt.figure(figsize=(20,5));
+plt.subplot(1, 2, 1 );
+plt.hist(y1);
+plt.xlabel('original target value')
+plt.ylabel('count')
+plt.subplot(1, 2, 2);
+plt.hist(y)
+plt.xlabel('aggregated target value')
+plt.show()