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Split the csv dataset into k folds for cross validation. def k _ fold _ cross _ validation ( dataset , k ) : n
Split the csv dataset into k folds for cross validation.
def kfoldcrossvalidationdataset k:
n lendataset # Length of the dataset
foldsize n k # Divide the length into smaller folds
folds # Empty list of folds
# Shuffle the dataset
shuffleddataset dataset.copy
random.shuffleshuffleddataset
for i in rangek:
# Assign a start and end variables in respect to the fold size
###
### YOUR CODE HERE
###
# Generate all the test indices for the current fold
testindices
###
### YOUR CODE HERE
###
# Generate all the train indices for the all other folds
trainindices
###
### YOUR CODE HERE
###
# Create a test set that is randomly populated via the testindices
testset
###
### YOUR CODE HERE
###
# Create a test set that is randomly populated via the trainindices
trainset
###
### YOUR CODE HERE
###
folds.appendtrainset, testset
return folds
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