how to prepare data for cross validation in mnist dataset?

Question

how to prepare data for cross validation in mnist dataset?

Boris

2022年1月13日 22:06

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.

Topic mnist keras cross-validation scikit-learn

Category Data Science

Vivek · Accepted Answer · 2020年8月7日 13:25

1

Vivek answered at 2020年8月7日 13:25

You can either validate your results on the test set or if you want to use KFold then you could first concatenate the train and test set first and then use KFold splitting to evaluate your results. Hope it helps!

Faraz Gerrard Jamal · Accepted Answer · 2018年7月18日 09:47

For the MNIST data,what you need to do is , apply cross validation on your training data for checking the performance of your model. Then, If you are satisfied by the performance of the model, you can train it on the whole training set. After that, you will use the trained model to make predictions for the test dataset.

Aditya · Accepted Answer · 2018年3月19日 06:37

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

They are not using the whole data for cross validation as such ( it's just an illusion)

When the cv argument is an integer, cross_val_score uses the KFold or StratifiedKFold strategies by default, the latter being used if the estimator derives from ClassifierMixin..

So it's kind of automated inside the call..

Check this kaggle kernel link

how to prepare data for cross validation in mnist dataset?

About