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

0 vote331 views1 answer
Python requests with login
Python
1 vote340 views1 answer
Les diviseurs d'un nombre python
Python
0 vote310 views3 answers
Detect player command block
Python
0 vote338 views1 answer
Setting up Colab for Kaggle Downloads
Python
0 vote311 views1 answer
Python file naming conventions
Python
10 votes328 views3 answers
Text to png python
Python
0 vote309 views1 answer
Python default summary statistics for all columns
Python
0 vote317 views1 answer
Copy multiple files from one folder to another folder
Python
0 vote309 views2 answers
UnicodeDecodeError: ‘utf8’ codec can’t decode byte
Python
0 vote297 views1 answer
Datetime.timedelta format to string python
Python