classify

This function allows to classify observations based on a pretrained model
that could have been obtained in several ways (such as using the train model
function). T

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

classify function

<dl><dt>data</dt>
<dd>The data to be classified. This data can be either the raw data
, or a MultiWaveAnalysis object generated earlier.</dd>
<dt>...</dt>
<dd>Additional arguments</dd></dl>

Arguments

Classifies observations based on a pretrained model. — classify

<dl>

<dt>data</dt>
<dd>The data to be classified. This data can be either the raw data
, or a MultiWaveAnalysis object generated earlier.</dd>


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

</dl>

classify: Classifies observations based on a pretrained model.

Description

Usage

Value

Arguments

See Also