def trainGradientBoosting(features, n_estimators):
 [X, Y] = listOfFeatures2Matrix(features)
 rf = sklearn.ensemble.GradientBoostingClassifier(n_estimators=n_estimators)
 rf.fit(X, Y)
 return rf

def trainGradientBoosting ( features , n_estimators ) : [ X , Y ] = listOfFeatures2Matrix ( features ) rf = sklearn . ensemble . GradientBoostingClassifier ( n_estimators = n_estimators ) rf . fit ( X , Y ) return rf
train a gradient boosting classifier note: this function is simply a wrapper to the sklearn functionality for svm training see function trainsvm_feature() to use a wrapper on both the feature extraction and the svm training processes .