#Kütüphaneleri yükle

import pandas as pd

import numpy as np

import matplotlib.pyplot as plt

from sklearn import preprocessing

from sklearn.linear_model import LogisticRegression

from sklearn.cross_validation import train_test_split

from sklearn.metrics import accuracy_score

from sklearn.metrics import f1_score

#Dosyayi Yukle

veri = pd.read_csv('veri/data_base.csv')

ozellik_sayisi = 20

#giris cikis belirle

giris_verileri = veri.iloc[:,1:ozellik_sayisi+1]

cikis = veri.iloc[:,-1]

#Egitim ve test verilerini ayir

egitim_giris, test_giris,egitim_cikis, test_cikis = train_test_split(giris_verileri,cikis, test_size=0.15, random_state=0)

#Standardizasyon

scaler = preprocessing.StandardScaler()

stdGiris = scaler.fit_transform(egitim_giris)

stdTest = scaler.transform(test_giris)

#Logistic Regression

log_reg = LogisticRegression(random_state=0)

log_reg.fit(stdGiris,egitim_cikis)

cikis_tahmin=log_reg.predict(stdTest)

#Baþarýyý belirle

basari = accuracy_score(test_cikis, cikis_tahmin)

fSkor =  f1_score(test_cikis, cikis_tahmin, labels=None, pos_label=1, average='binary', sample_weight=None)