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I am performing nested cross-validation, and I know that the idea behind it is to see how the model generalizes. For that, we don't only shuffle the training data but we also do shuffle the testing da …

I have read very well the awesome answers and suggestions by @cbeleites and @Dikran Marsupial here for nested CV but I am still confused about something: Basically now I understand that nested CV is n …

I am implementing cross validation and calculating error metrics such as RMSE, $R^2$, MAE, MSE, etc. Can RMSE and MAE have the same value?

I am running k-fold cross validation on my training data, and then choosing the best set of hyper parameters, re-training on the training data and testing on a new (unseen) testing data. I am getting …

I am running repeated K-fold Cross-Validation on my dataset using different models. My problem is a regression problem and I am counting on the error metric MAE. I do know that some models may behave …

I am running 10-folds 10 repeats cross validation over my data. I am using XGBoost Classifier with hyper parameter tuning. The learning curve looks as follows: However, both the training and validat …

I have implemented cross validation function with hyper parameter tuning. Basically, doing the following: Split the data into 80% training, 20% testing apply cross validation with hyper parameter tu …

After a bit of research I found out that I can use pipeline in order to avoid data leakage. references: this and this This is how my code looks like now: def produce_learning_curve(self, model, mo …

I have a time-series data that I want to model using machine learning models like Lasso Regression, Ridge, elastic net, etc. However, in order to make it stationary, I difference the output variable, …

I have a time series data that I wish to be able to obtain the general performance of it. For that, I use nested cross-validation with time series flavor as described in this amazing blog. As you hav …

@cbeleites Thank you so much!!! Indeed I realize what you are saying is very very true. The reason why I did not using rolling forecasts directly is because I have suite of models: Lasso, Ridge.., et …