Train dev test split sklearn

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)

Sklearn train_test_split

 import numpy as np
 from sklearn.model_selection import train_test_split


X_train, X_test, y_train, y_test = train_test_split(
  X, y, test_size=0.33, random_state=42
)

Train dev test split sklearn

train, validate, test = np.split(df.sample(frac=1), [int(.6*len(df)), int(.8*len(df))])

Source: datascience.stackexchange.com

Similar codes

1 vote185 views2 answers
Pytorch l2 regularization
Python
0 vote179 views1 answer
Pytz: No module named 'pytz'
Python
15 votes155 views4 answers
Cv2 show image
Python
4 votes182 views1 answer
Find text between two strings regex python
Python
13 votes156 views3 answers
Django form example
Python
1 vote211 views1 answer
Git clone in python to tmp directory
Python
1 vote163 views2 answers
Changing default python version ubuntu
Python
0 vote188 views4 answers
Create a python for loop that sums the numbers from 100 to 200
Python
0 vote159 views1 answer
Get users except superuser django
Python
0 vote185 views1 answer
Supercharged python
Python