Note
Click here to download the full example code
Train test split with every kind of cross-validation¶
This example shows how to split between test and train according to every cross-validation method.
Import librairies¶
import numpy as np
import museotoolbox as mtb
Generate random dataset¶
np.random.seed(42)
y = np.random.randint(1,3,10)
X = np.random.randint(1,255,[10,3],dtype=np.uint8)
Split train/test¶
Using museotoolbox.cross_validation.LeaveOneOut
cv = mtb.cross_validation.LeaveOneOut(random_state=42)
X_train, X_test, y_train, y_test = mtb.cross_validation.train_test_split(cv,X,y)
Split train/test with groups¶
Generate group
groups = np.array([1, 1, 2, 3, 4, 2, 1, 1, 2, 3],dtype=int)
Using museotoolbox.cross_validation.LeaveOneSubGroupOut
cv = mtb.cross_validation.LeaveOneSubGroupOut(random_state=42)
X_train, X_test, y_train, y_test, g_train, g_test = mtb.cross_validation.train_test_split(cv,X,y,groups=groups)
Total running time of the script: ( 0 minutes 0.002 seconds)