Python for Finance Cookbook

How to do it...

Execute the following steps to fit a decision tree classifier.

1. Import the libraries:

from sklearn.tree import DecisionTreeClassifier, export_graphvizfrom sklearn import metricsfrom chapter_8_utils import performance_evaluation_reportfrom io import StringIOimport seaborn as snsfrom ipywidgets import Imageimport pydotplus 

2. Create an instance of the model, fit it to the training data, and create the prediction:

tree_classifier = DecisionTreeClassifier()tree_classifier.fit(X_train_ohe, y_train)y_pred = tree_classifier.predict(X_test_ohe)

3. Evaluate the results:

LABELS = ['No Default', 'Default']tree_perf = performance_evaluation_report(tree_classifier,                                           X_test_ohe,                                           y_test, labels=LABELS,                                           show_plot=True)

Running the code ...