[Python] Python mlExtend cross_val error on cross validation. : 'index 5 is out of bounds for...

I´m trying to do a cross validation with OneRClassifier. I use from sklearn.model_selection import KFold, train_test_split, cross_val_score for cross validation. I have four dimensional data for starters. The fourth is the label column and first three are features. This is the print for the X also known as features when encoded with label encoder:

[[ 0 0 9]
[ 0 6 9]
[ 0 3 8]
[ 0 9 4]
[ 0 3 8]
[ 0 9 12]
[ 0 1 2]
[ 0 0 0]
[ 0 9 5]
[ 0 7 12]
[ 0 5 13]
[ 0 3 1]
[ 0 9 8]
[ 0 5 13]
[ 0 0 11]
[ 0 3 7]
[ 0 10 14]
[ 0 2 4]
[ 0 4 3]
[ 0 3 4]
[ 0 3 12]
[ 0 3 13]
[ 0 8 10]
[ 0 8 4]
[ 0 8 1]
[ 0 8 13]
[ 0 3 8]
[ 0 4 6]
[ 0 5 1]
[ 0 2 12]]


This is the print for the y

[5 2 5 0 5 0 5 5 0 2 5 1 0 5 5 5 3 5 5 5 5 1 5 5 5 5 5 5 4 5]


The shapes are for X (30, 3) and for y (30,).

accuraciesOneR = cross_val_score(oneR, X, y, cv=kf, scoring='accuracy', error_score='raise')


This produces an error 'index 5 is out of bounds for axis 0 with size 3' on the cross validation. As i can see the shapes are correct. However i might be wrong. If you can advice me please.

This is a cross validation of data with oneR in python. I expected the cross validation to work without errors and give me results.

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