Linked Questions

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: ...
3
votes
1answer
876 views

Compare different classification algorithms after hyperparameter tuning

Let's say I have a classification problem with $c$ classes. For this, I have a data set containing $N$ distinct feature vectors with $n$ features. Let's say $N$ is of the order of $10^5$, and both $c$ ...
0
votes
1answer
89 views

How can I conclude my model performance?

I use cross validation to find a best set of parameters for random forest on my dataset. Then I use the best model to fit my train set and got an average AUC of 0.6883. But I can see the variability ...
0
votes
1answer
835 views

Model selection: before or after nested cross-validation?

I want to build a neural network over a data set. My idea is to use cross-validation on a training set to select the "best" neural network (and evaluate it on a separate test set) and to use nested ...
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-...
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 ...
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 ...
3
votes
1answer
275 views

Cross-validation scheme used in the Introduction to Statistical Learning, Chapter 6, Lab 3

I've been really enjoying the Introduction to Statistical Learning textbook so far, and I'm currently working my way through chapter 6. I realize that I am very confused by the process used in lab 3 ...
0
votes
1answer
261 views

K-fold CV based model selection with a constraint on the number of features?

I am currently working on project where I need to train a logistic regression classifier with a combined $l_1$/$l_2$-penalty that satisfies a hard on the number of features. Specifically, my dataset ...
1
vote
2answers
1k views

Model prediction: test for difference in MSE

I have made two regression models. They were made on a training set of 80% of the data. And 20% of the data is the validation set. No test set is made. The models tell me how much premium a ...
5
votes
1answer
430 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 ...
0
votes
1answer
55 views

Performance of a classifier change heavily

I'm using a data set of 32 face persons and a svm-rbf to classify and a random group of 70% for train and 30% for test. The problem is that my results are heavily dependent of the random group used ...
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 ...
4
votes
2answers
3k views

Is cross validation needed?

Suppose we have training data set and a test data set. The outcome variable is binary. Is it usually necessary to split the training data set so that there is a cross validation data set? Or can you ...
18
votes
1answer
12k 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 ...

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