#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Dec 22 15:25:33 2018

@author: zoso
"""

# Importing the libraries

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

# Importing the dataset
dataset = pd.read_csv("Data.csv")
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, -1].values

# Splitting the data into Training Set and Test set
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)

# Data Scaling
"""from sklearn.preprocessing import StandardScaler
sc_X = StandardScaler()
X_train = sc_X.fit_transform(X_train)
X_test = sc_X.transform(X_test)"""


#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Dec 22 15:25:33 2018

@author: zoso
"""

# Importing the libraries

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

# Importing the dataset
dataset = pd.read_csv("Data.csv")
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, -1].values

# Splitting the data into Training Set and Test set
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)

# Data Scaling
"""from sklearn.preprocessing import StandardScaler
sc_X = StandardScaler()
X_train = sc_X.fit_transform(X_train)
X_test = sc_X.transform(X_test)"""


#!/usr/bin/env python3 # -*- coding: utf-8 -*- Created on Sat Dec 22 15:25:33 2018  @author: zoso # Importing the libraries # Importing the dataset # Splitting the data into Training Set and Test set # Data Scaling from sklearn.preprocessing import StandardScaler sc_X = StandardScaler() X_train = sc_X.fit_transform(X_train) X_test = sc_X.transform(X_test)