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Cross Validation and hyperparameter selection correct procedure

I am trying to run a regression supervised learning problem. The dataset is not very large and I wanted to do some cross-validation to avoid overfitting. As I have read it's important to do a ...
metc's user avatar
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1 answer
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Is it valid to implement hyper-parameter tuning and THEN cross-validation?

I have a multi-label classification task I am solving. I have done hyperparameter tuning (with Keras Tuner) to determine the best configuration for my neural network. Is it valid to do this (determine ...
user9317212's user avatar
2 votes
1 answer
121 views

After having selected the best model with cross-validation, for how long should I train it?

When using k-fold cross-validation in a deep learning problem, after you have computed your hyper-parameters, how do you decide how long to train your final model? My understanding is that, after the ...
FourierFlux's user avatar
1 vote
1 answer
106 views

How to fairly conduct a model performance with 5-fold cross validation after augmentation?

I have, say, a (balanced) data-set with 2k images for binary classification. What I have done is that randomly divided the data-set into 5 folds; copy-pasted all 5-fold data-set to have 5 exact ...
bit_scientist's user avatar
16 votes
1 answer
402 views

Will parameter sweeping on one split of data followed by cross validation discover the right hyperparameters?

Let's call our dataset splits train/test/evaluate. We're in a situation where we require months of data. So we prefer to use the evaluation dataset as infrequently as possible to avoid polluting our ...
Philipp Cannons's user avatar