import pandas as pd
import numpy as np
from sklearn.ensemble import AdaBoostClassifier
from sklearn.ensemble import RandomForestClassifier

test = pd.read_csv('../input/test.csv')
train = pd.read_csv('../input/train.csv')

clf = RandomForestClassifier(n_estimators=1000,n_jobs=-1);

bclf = AdaBoostClassifier(base_estimator=clf,n_estimators=clf.n_estimators)

trainLabel = train.label
train = train.drop('label',1)

bclf.fit(train,trainLabel)

dt = bclf.predict(test)

predictions = pd.DataFrame(data=dt,columns=["label"])
predictions["ImageId"] = list(range(1,len(test)+1))

predictions.to_csv("sklearn_decisiontree.csv",index=False)