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()
