Jul 4, 2021 · I am trying to get a deeper understanding of the common ML pipelines and I have some doubts regarding Cross Validation, why do we really use it and what does it really tell us about Bias …

Jun 27, 2014 · K-fold cross-validation seems to give better approximations of generalization (as it trains and tests on every point). So, why would we use the standard hold-out validation?

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Dec 21, 2012 · The nested cross validation is to use. It is understood that the K-1 fold data is as training data and left fold is as test data. to find the optimal hyperparameters. the k-1 fold data (training data …

Jun 9, 2015 · It certainly makes sense, & although LASSO only optimizes over one (hyper-)parameter, if you want to get the best estimate you can of out-of-sample performance you need an outer cross …

Jun 29, 2022 · Trying to teach myself cross-validation on a super simple example, linear regression. My understanding is that when I build a model via CV, it should have a lower RMSE. But I find almost …

Oct 17, 2020 · Cross validation is internal in both senses, since the test cases are randomly selected from the same data set on which training is performed. A validation study testing a ready-to-use …

Jul 19, 2020 · Cross-validation keeps the don't-reward-an-exact-fit-to-training-data advantage of the training-testing split, while also using the data that you have as efficiently as possible (i.e. all of your …

Thanks for the reply Simon. I actually figured out the problem later - turns out, the parameter for "model" in cross_val_score is simply an object of the classifier/model, and nothing else - irrespective of …

Sep 11, 2018 · I am dealing with a similar problem at the moment, that is how best to pick a window size. Which approach did you go with and what were your results?Did you encounter any problems …