from sklearn.ensemble import GradientBoostingClassifier
import pandas as pd

data = pd.read_csv("../data/data.csv", header=0)

X = data.iloc[:,1:-1]
y = data.iloc[:,0]

gbdt = GradientBoostingClassifier(criterion='friedman_mse', init=None,
          learning_rate=0.1, loss='deviance', max_depth=3,
          max_features=None, max_leaf_nodes=None,
          min_impurity_split=1e-07, min_samples_leaf=1,
          min_samples_split=2, min_weight_fraction_leaf=0.0,
          n_estimators=90, presort='auto', random_state=None,
          subsample=1.0, verbose=0, warm_start=False)

gbdt.fit(X, y)

import pydotplus
from sklearn import tree

for i in range(gbdt.estimators_.shape[0]):
    dot_data = tree.export_graphviz(gbdt.estimators_[i][0], out_file=None)
    graph = pydotplus.graph_from_dot_data(dot_data)
    graph.write_pdf("../data/trees/tree_"+str(i)+".pdf")