partial_dep_lot_loan_data.py

# Plot partial dependence plots
gbrt = GradientBoostingClassifier(loss="deviance",
                                  learning_rate=0.1,
                                  n_estimators=100,
                                  max_depth=3,
                                  random_state=123)
gbrt.fit(X_res, y_res)
fig, axes = plot_partial_dependence(gbrt,
                                    X_res,
                                    np.argsort(gbrt.feature_importances_)[::-1][:8],
                                    n_cols=4,
                                    feature_names=df.columns[:-6],
                                    figsize=(14, 8))
plt.subplots_adjust(top=0.9)
plt.suptitle("Partial dependence plots of borrower not fully paid\n" + 
             "the loan based on top most influential features")
for ax in axes:
  ax.set_xticks(())