Hands-On Machine Learning for Cybersecurity

Gini coeffiecient

The following code shows the gini coefficient:

DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=7,            max_features=None, max_leaf_nodes=None,            min_impurity_decrease=0.0, min_impurity_split=None,            min_samples_leaf=1, min_samples_split=2,            min_weight_fraction_leaf=0.0, presort=False, random_state=None,            splitter='best')

To visualize the results of the decision with a graph, use the graphviz function:

export_graphviz(treeclf, out_file='tree_kdd.dot', feature_names=X.columns)

At the command line, we run this into convert to PNG:

# dot -Tpng tree_kdd.dot -o tree_kdd.png

We then extract the feature importance:

pd.DataFrame({'feature':X.columns, 'importance':treeclf.feature_importances_}).sort_values('importance', ...