# -*- coding: utf-8 -*-
"""
Created on Mon Feb 19 00:55:43 2018

@author: arnbj
"""
#Nota kóða úr glærupakka 8!!!


from sklearn.datasets import fetch_mldata

#Sækjum gagnasettið
mnist = fetch_mldata('MNIST original')
X, y = mnist["data"], mnist["target"]

from sklearn import model_selection


#Skiptum i þjalfunar og profunargagnasett
Xtrain, Xtest, ytrain, ytest = model_selection.train_test_split(X, y, test_size = 0.2)

from sklearn.ensemble import RandomForestClassifier
from sklearn.ensemble import ExtraTreesClassifier
from sklearn.ensemble import VotingClassifier
from sklearn.metrics import accuracy_score
from sklearn.linear_model import LogisticRegression

#Skilgreinum módel

et_clf = ExtraTreesClassifier()
rf_clf = RandomForestClassifier()
lr_clf = LogisticRegression()

voting_hard_clf = VotingClassifier(estimators=[('et', et_clf), ('rf', rf_clf), ('lr', lr_clf)], voting='hard')
voting_soft_clf = VotingClassifier(estimators=[('et', et_clf), ('rf', rf_clf), ('lr', lr_clf)], voting='soft')


for clf in (et_clf, rf_clf, lr_clf):
    clf.fit(Xtrain, ytrain)
    y_pred = clf.predict(Xtest)
    print(clf.__class__.__name__, accuracy_score(ytest, y_pred))