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
