Getting indices while using train test split in scikit

Question

In order to split my data into train and test data separately, I'm using

sklearn.cross_validation.train_test_split function.

When I supply my data and labels as list of lists to this function, it returns train and test data in two separate lists.

I want to get the indices of the train and test data elements from the original data list.

Can anyone help me out with this?

Thanks in advance

Answer 1

You can supply the index vector as an additional argument. Using the example from sklearn:

import numpy as np
from sklearn.cross_validation import train_test_split
X, y,indices = (0.1*np.arange(10)).reshape((5, 2)),range(10,15),range(5)
X_train, X_test, y_train, y_test,indices_train,indices_test = train_test_split(X, y,indices, test_size=0.33, random_state=42)
indices_train,indices_test
#([2, 0, 3], [1, 4])