Created
July 22, 2018 19:47
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Steps followed for preprocessing the data for ML
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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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