cross_vfold_ts: Generate cross-validated time-series K-fold test-training...

In jrnold/ramsleep: Resampling, Cross-Validation, and Permutation Methods Infrastucture

Description

Splits data into test/train sets for cross-validating time series data. In each split, the indices are increasing, so only previous data are used to test future data.

Usage

cross_vfold_ts(n, v = 5L)

Arguments

n	A positive, scalar integer representing the number of observations (items to choose from).
v	A scalar integer representing the number of folds to generate.

Details

The data are split into K ≥q 2 folds, where for each i in 2:K, the i-th fold is the test set and folds 1, ..., (i - 1) folds are the training set.

References

• Scikit-learn v. 0.18.1. Cross-validation: evaluating estimator performance. URL.

jrnold/ramsleep documentation built on May 29, 2019, 11:43 a.m.