cross-validation set vs cross-validation data set

Both "cross-validation set" and "cross-validation data set" are correct phrases. The choice between them depends on the level of detail you want to convey. "Cross-validation set" is more concise and commonly used, while "cross-validation data set" provides additional clarity by explicitly mentioning that it is a data set used for cross-validation.

Last updated: March 19, 2024 • 840 views

This phrase is correct and commonly used in the context of machine learning and data analysis.

"cross-validation set "

This phrase refers to a subset of data used for cross-validation, a technique for assessing how well a model generalizes to new data.

Examples:

Make sure to split your dataset into a training set, a validation set, and a cross-validation set.

Show examples from the web [+]

Nov 28, 2011 ... ++Cross-Validation set (20% of the original data set): This data set is used to compare the performances of the prediction algorithms that were ...
Sep 1, 2014 ... Training set size as 50; Cross validation set size 25, and; Test size as 25. But probably this makes more or less sense. How should I really ...
Minimize cost function for each of the models as before; Test these hypothesis on the cross validation set to generate the cross validation error; Pick the ...
The error is evaluated on the cross-validation set, and the meta-parameters (in our case, the degree of the polynomial) are adjusted so that this cross-validation ...

Alternatives:

validation set
test set

This phrase is also correct and provides more specificity by explicitly mentioning that it is a data set used for cross-validation.

"cross-validation data set "

This phrase can be used when you want to emphasize that the data set is specifically designated for cross-validation purposes.

Examples:

Ensure that the cross-validation data set covers a representative sample of the overall data distribution.

Show examples from the web [+]

Oct 17, 2012 ... Even if you want to simply select an algorithm that gives you highest F1 score, you'd need to use extra cross validation data set to do that.
Jul 16, 2014 ... Is it usually necessary to split the training data set so that there is a cross validation data set? Or can you use the whole training data set to build ...
... this is pretty much what you'd expect, just like the training error you've set measure it on a cross validation data set, and here's my test set error same as before ...
Before we describe the functions to create the cross validation data set we present a small usage example that tries to find a good regularization parameter for a ...

Alternatives:

cross-validation set
validation data set
test data set

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cross-validation set vs cross-validation data set