Faq choose between different cross validation leave out options

From Eigenvector Research Documentation Wiki
Revision as of 13:15, 8 January 2019 by imported>Lyle (→‎Possible Solutions:)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search

Issue:

How do I choose between the different cross-validation leave-out options?

Possible Solutions:

There are many attributes that influence selection of the appropriate cross-validation scheme for a given situation:

  • The ordering of the samples in the dataset,
  • The total number of objects (and variables) in the dataset
  • The presence (or lack thereof) of replicate samples in the dataset
  • The specific objective(s) of the analysis,
  • The consequences/costs of overly optimistic or overly pessimistic results, and
  • The amount of time available to do cross-validation

For details on the different methods, see our Wiki page: Using Cross-Validation and, in particular, Choosing the Cross-Validation Method


Still having problems? Please contact our helpdesk at helpdesk@eigenvector.com