Using this knowledge, write a function which uses sklearn's KFold class internally, and that will take as input a 2-d numpy array and an integer K corresponding to the number of splits. This function will then return a list of tuples of length K. Each tuple in this list should consist of a train_indices list and a test_indices list containing the training/testing data point indices for that particular Kth split. Function Specifications: Should take a 2-d numpy array and an integer K as input. Should use sklearn's KFold class. Should return a list of K tuples containing a list of training and testing indices corresponding to the data points that belong to a particular split. For example, given an array called data and an integer K, the function should return: data_indices = [(list_of_train_indices_for_split_1, list_of_test_indices_for_split_1) (list_of_train_indices_for_split_2, list_of_test_indices_for_split_2) (list_of_train_indices_for_split_3, list_of_test_indices_for_split_3) ... ... (list_of_train_indices_for_split_K, list_of_test_indices_for_split_K)] The shuffle argument in the KFold object should be set to False. ### START FUNCTION def sklearn_kfold_split(data,K): # your code here return ### END FUNCTION

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Using this knowledge, write a function which uses sklearn's KFold class internally, and that will take as input a 2-d numpy array and an integer K corresponding to the number of splits. This function will then return a list of tuples of length K. Each tuple in this list should consist of a train_indices list and a test_indices list containing the training/testing data point indices for that particular Kth split.

Function Specifications:

Should take a 2-d numpy array and an integer K as input.
Should use sklearn's KFold class.
Should return a list of K tuples containing a list of training and testing indices corresponding to the data points that belong to a particular split. For example, given an array called data and an integer K, the function should return:
data_indices = [(list_of_train_indices_for_split_1, list_of_test_indices_for_split_1)
                (list_of_train_indices_for_split_2, list_of_test_indices_for_split_2)
                (list_of_train_indices_for_split_3, list_of_test_indices_for_split_3)
                                                 ...
                                                 ...
                (list_of_train_indices_for_split_K, list_of_test_indices_for_split_K)]
The shuffle argument in the KFold object should be set to False.
### START FUNCTION

def sklearn_kfold_split(data,K):

# your code here

return

### END FUNCTION

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