from sklearn import cross_validation from sklearn.ensemble import RandomForestClassifier, ExtraTreesClassifier, AdaBoostClassifier, \ GradientBoostingClassifier from sklearn.grid_search import GridSearchCV from sklearn.svm import SVC from sklearn.tree import DecisionTreeClassifier from Classifier import Classifier import numpy as np #base model name = 'RF_500_5' model = RandomForestClassifier(n_estimators=500, max_features='auto', max_depth=None, min_samples_split=5.5, bootstrap=True, oob_score=True, n_jobs=-1, verbose=True, random_state=0) clf = Classifier(model, name, one_hot=False, drop_cat=False, calibration=False, create_submission=True) clf.run() clf.plot_importance()