Questions tagged [k-fold-cv]

For questions related to the k-fold cross-validation technique, where you split the dataset into k folds (subsets), train the model on k - 1 of these folds and test it on the remaining (test) fold; then repeat this procedure for each of the k folds, such that we compute the test performance for each fold; finally, we can average these test performances.

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Why would the "improvement" be the result of random initialization, and so why should we use multiple runs?

I got this feedback for my thesis paper. The improvement shown in the results section could be the result of random initialization. There should be multiple runs with means and standard deviations. ...
5
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3answers
603 views

Is k-fold cross-validation more effective than splitting the dataset into training and test datasets to prevent overfitting?

I want to prevent my model from overfitting. I think that k-fold cross-validation (because it is doing this each time with different datasets) may be more effective than splitting the dataset into ...
7
votes
1answer
183 views

What is the best measure for detecting overfitting?

I wanted to ask about the methodology of testing the ML models against overfitting. Please note that I don't mean any overfitting reducing methods like regularisation, just a measure to judge whether ...
1
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1answer
116 views

Is it possible to combine k-fold cross-validation and oversampling for a multi-class text classification task with imbalanced data?

I am dealing with an intent classification task on an Italian customer service data set. I've more or less 1.5k sentences and 29 classes (imbalanced). According to the literature, a good choice is to ...