Linked Questions

26
votes
4answers
10k views

Internal vs external cross-validation and model selection

My understanding is that with cross validation and model selection we try to address two things: P1. Estimate the expected loss on the population when training with our sample P2. Measure and report ...
20
votes
4answers
5k views

How bad is hyperparameter tuning outside cross-validation?

I know that performing hyperparameter tuning outside of cross-validation can lead to biased-high estimates of external validity, because the dataset that you use to measure performance is the same one ...
18
votes
1answer
11k views

How is the confusion matrix reported from K-fold cross-validation?

Suppose I do K-fold cross-validation with K=10 folds. There will be one confusion matrix for each fold. When reporting the results, should I calculate what is the average confusion matrix, or just sum ...
17
votes
4answers
18k views

Cross validation and parameter tuning

Can anyone tell me what exactly a cross-validation analysis gives as result? Is it just the average accuracy or does it give any model with parameters tuned? Because, I heard somewhere that cross-...
17
votes
1answer
2k views

How to build the final model and tune probability threshold after nested cross-validation?

Firstly, apologies for posting a question that has already been discussed at length here, here, here, here, here, and for reheating an old topic. I know @DikranMarsupial has written about this topic ...
16
votes
3answers
5k views

How to get hyper parameters in nested cross validation?

I have read the following posts for nested cross validation and still am not 100% sure what I am to do with model selection with nested cross validation: Nested cross validation for model selection ...
10
votes
1answer
14k views

How to do cross-validation with cv.glmnet (LASSO regression in R)?

I'm wondering how to approach properly training and testing a LASSO model using glmnet in R? Specifically, I'm wondering how to do so if a lack of an external test data set necessitates I use cross-...
9
votes
2answers
4k views

Nested cross-validation - how is it different from model selection via kfold CV on the training set?

I often see people talking about 5x2 cross-validation as a special case of nested cross validation. I assume the first number (here: 5) refers to the number of folds in the inner loop and the second ...
9
votes
2answers
8k views

Implementation of nested cross-validation

I'm trying to figure out if my understanding of nested cross-validation is correct, therefore I wrote this toy example to see if I'm right: ...
8
votes
1answer
2k views

How to obtain optimal hyperparameters after nested cross validation?

In general, if we have a large dataset, we can split it into (1) training, (2) validation, and (3) test. We use validation to identify the best hyperparameters in cross validation (e.g., C in SVM) and ...
7
votes
1answer
2k views

CV for model parameter tuning AND then model evaluation

I have a basic question on using cross-validation for model parameter tuning (model training) and model evaluation (testing) similar to this Model Tuning and Model Evaluation in Machine Learning I ...
7
votes
1answer
59 views

An Information Criterion that considers how many variables we can choose from

I am running a multiple regression model and looking to use AIC and BIC to select models. However I notice that both measures do not consider the number of variables we can choose from but only ...
6
votes
1answer
856 views

Nested cross validation vs repeated k-fold

I know there are many topics(1,2,3), papers(1,2,3) and websites(1) that discuss this topic at length. However for the past two days I am reading all I can find about the subject and seems I hit a ...
5
votes
1answer
424 views

What is the standard procedure for evaluating a user-based CF algorithm with a dataset offline?

I have read some papers and other materials about the evaluation of recommender systems (RS). Most of them discuss the various properties of RS (e.g. accuracy, diversity, etc.), and metrics for ...
5
votes
2answers
483 views

Which gamma regression model to use for extrapolation?

I'm looking for a regression model which would satify these requirements: My target variable follows the exponential distribution, so to my understanding I should use gamma loss function. I have ...

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