KFCV

This function performs the K-Fold Cross Validation (KFCV) process
with different types of input parameters.

The library allows to perform a multivariate time series
classification based on the use of Discrete Wavelet Transform for
feature extraction, a step wise discriminant to select the most
relevant features and finally, the use of a linear or quadratic
discriminant for classification. Note that all these steps can be done
separately which allows to implement new steps. Velasco, I., Sipols,
A., de Blas, C. S., Pastor, L., & Bayona, S. (2023)
<doi:10.1186/S12938-023-01079-X>. Percival, D. B., & Walden, A. T.
(2000,ISBN:0521640687). Maharaj, E. A., & Alonso, A. M. (2014)
<doi:10.1016/j.csda.2013.09.006>.

Iván Velasco

TSEAL

Time Series Analysis Library

KFCV function

<dl><dt>data</dt>
<dd>Starting data to generate the validation. It can be either the
raw data, or a previously generated MultiWaveAnalysis object.</dd>
<dt>...</dt>
<dd>Additional arguments</dd></dl>

Arguments

K-Fold Cross Validation (KFCV) — KFCV

<dl>

<dt>data</dt>
<dd>Starting data to generate the validation. It can be either the
raw data, or a previously generated MultiWaveAnalysis object.</dd>


<dt>...</dt>
<dd>Additional arguments</dd>

</dl>

KFCV: K-Fold Cross Validation (KFCV)

Description

Usage

Value

Arguments

See Also