How to use k-fold cross validation for MNIST dataset? I read article documentation on sci-kit learn ,in that example they used the whole iris dataset for cross validation.
from sklearn.model_selection import cross_val_score clf = svm.SVC(kernel='linear', C=1) scores = cross_val_score(clf, iris.data, iris.target, cv=5) scores
for example while importing mnist dataset in keras
from keras.datasets import mnist (Xtrain,Ytrain),(Xtest,Ytest)=mnist_load()
in this dataset is already divided in test and train , so to apply cross validation on the entire dataset do we need to make Xtrain and Xtest as one entity to exploit the whole data.