April 2018
Beginner to intermediate
282 pages
6h 52m
English
The following code snippet will allow you to examine the decision boundaries of different types of algorithms:
import matplotlib.cm as cm# This function will scale training datatset and train given classifier.# Based on predictions it will draw decision boundaries.def draw_decision_boundary(clf, X, y, h = .01, figsize=(9,9), boundary_cmap=cm.winter, points_cmap=cm.cool): # After you apply StandardScaler, feature means will be removed and all features will have unit variance. from sklearn.preprocessing import StandardScaler X = StandardScaler().fit_transform(X) # Splitting dataset to train and test sets. X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.4, random_state=42) # Training given estimator ...