Question : train test split sklearn
Answered by : al
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)Source : | Last Update : Sun, 15 Nov 20
Question : test split
Answered by : gabriel-juri
import numpy as np
from sklearn.model_selection import train_test_split
# Data example
X, y = np.arange(10).reshape((5, 2)), range(5)
# Split data into train and test sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)Source : https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html | Last Update : Wed, 04 May 22
Question : scikit learn train test split
Answered by : aggressive-anaconda-x0uk07g3homs
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)Source : https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html | Last Update : Tue, 08 Dec 20