Python for Finance Cookbook

How to do it...

Execute the following steps to train the advanced classifiers.

1. Import the libraries:

from sklearn.ensemble import (RandomForestClassifier,                               GradientBoostingClassifier)from xgboost.sklearn import XGBClassifierfrom lightgbm import LGBMClassifier

2. Define and fit the Random Forest pipeline:

rf = RandomForestClassifier(random_state=42)
rf_pipeline = Pipeline(steps=[('preprocessor', preprocessor),
                              ('classifier', rf)
                             ])rf_pipeline.fit(X_train, y_train)rf_perf = performance_evaluation_report(rf_pipeline, X_test,                                         y_test, labels=LABELS,                                         show_plot=True,                                        show_pr_curve=True)

The performance of the Random Forest can be summarized by the following plot:

3. Define and fit the Gradient Boosted Trees pipeline:

gbt =  GradientBoostingClassifier ...