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

10 votes199 views2 answers
Browser refresh selenium python
Python
-2 votes186 views1 answer
Client server python socket
Python
37 votes173 views1 answer
Time format conversion in python
Python
45 votes207 views4 answers
Append to front of list python
Python
0 vote169 views1 answer
Normalize rows in matrix numpy
Python
13 votes640 views4 answers
AttributeError: module 'tensorflow' has no attribute 'Session'
Python
5 votes183 views3 answers
Python import graphviz
Python
0 vote168 views1 answer
Python convert png to jpg
Python
0 vote188 views1 answer
Get return value of contract call in brownie
Python
1 vote229 views1 answer
Python match phone number
Python