Usage Note 36388: How are the crossvalidation statistics defined in Partition?
The k-fold crossvalidation method randomly divides all of the (non-excluded) rows in the datatable, D, into k subsets: D1, D2, . . . , Dk. Each row is randomly assigned to one of the k groups.
Note: This means that for k=n (the sample size), some groups have several rows, and many groups have none.
First, a model is fit using all of the data. Then, K different models are fit, using the same splits, with data from D - Di, where Di is the holdout fold. For continuous responses, the error for each observation in Di is calculated using the model, evaluated from D - Di. For nominal and ordinal responses, JMP® calculates -2LogLikelihood for each observation in Di using the model, trained from D - Di. This is repeated for each of the k folds. The root mean square errors for each of the k folds are squared and summed (or in the case of nominal and ordinal responses, the -2loglikelihood values are summed) to construct the crossvalidation SSE (or crossvalidation -2loglikelihood in the case of nominal and ordinal responses). The resulting folded SSE is then used to calculate a folded R square value.
Operating System and Release Information
|Product Family||Product||System||SAS Release|
|JMP Software||JMP software||Windows 7 Professional 32 bit|
|Windows 7 Professional x64|
|Windows 7 Ultimate 32 bit|
|Windows 7 Home Premium x64|
|Windows 7 Home Premium 32 bit|
|Windows 7 Enterprise x64|
|Windows 7 Enterprise 32 bit|
|Microsoft Windows 10|
|Microsoft Windows 8.1 Pro x64|
|Microsoft Windows 8.1 Pro 32-bit|
|Microsoft Windows 8.1 Enterprise x64|
|Microsoft Windows 8.1 Enterprise 32-bit|
|Microsoft Windows 8 Pro x64|
|Microsoft Windows 8 Pro 32-bit|
|Microsoft Windows 8 Enterprise x64|
|Microsoft Windows 8 Enterprise 32-bit|
|Microsoft® Windows® for x64|
|Macintosh on x64|
|Windows 7 Ultimate x64|
|Date Modified:||2009-06-28 13:38:04|
|Date Created:||2009-06-26 15:18:44|