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- # Data Preprocessing Template
- # 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[:, 3].values
- # Splitting the dataset into the 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)
- # Feature Scaling
- """from sklearn.preprocessing import StandardScaler
- sc_X = StandardScaler()
- X_train = sc_X.fit_transform(X_train)
- X_test = sc_X.transform(X_test)
- sc_y = StandardScaler()
- y_train = sc_y.fit_transform(y_train)"""
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