train test split sklearn
from sklearn.model_selection import train_test_split
X = df.drop(['target'],axis=1).values # independant features
y = df['target'].values # dependant variable
# Choose your test size to split between training and testing sets:
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)what is random state
The random state is simply the lot number of the set generated randomly in any operation. We can specify this lot number whenever we want the same set again.Copyright © 2021 Codeinu
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