plt.xlabel('Iterations') plt.ylabel('Deviance') plt.show() # <codecell> #Correlation matrix report.features_correlation_matrix().plot(show_legend=False) # <codecell> #Features histogramms hist_var = variables[:] hist_var.remove(u'NbTape') hist_var.remove(u'TapeSize') report.features_pdf(features=hist_var, bins = 10).plot() # <codecell> #ROC - curve report.roc().plot(xlim=(0, 1)) # <codecell> # define metric functions from sklearn.metrics import accuracy_score from sklearn.metrics import f1_score from sklearn.metrics import precision_score import numpy