from sklearn.ensemble import RandomForestClassifier
from sklearn.linear_model import LogisticRegressionCV
from sklearn.naive_bayes import GaussianNB
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.linear_model import SGDClassifier
##################################################
data = pd.read_csv("data6.txt")
x = data.iloc[:, :-1].values
y = data.iloc[:, -1].values
'''
import matplotlib.pyplot as plt
plt.scatter(x , y)
plt.show(')
'''
y = lp.LABLEENCODER(y, 2)
'''
from sklearn.preprocessing import StandardScaler
scale = StandardScaler()
x2 = scale.fit_transform(x)
'''
##################################################
def TRAIN_TEST_SPLIT(X_var, Y_var, TEST_SIZE=None, RAND_STATE=None):
if TEST_SIZE == None:
TEST_SIZE = randint(1, 3) * 10
try:
from sklearn.cross_validation import train_test_split
except DeprecationWarning as e:
print(e, "NEED TO BE CHECKED !")
