do_fit

Generic for fitting a time series model.
Descendants should implement <code>do_fit.&lt;class&gt;</code>.

Time series prediction is a critical task in data analysis, requiring not only the selection of appropriate models, but also suitable data preprocessing and tuning strategies.
TSPredIT (Time Series Prediction with Integrated Tuning) is a framework that provides a seamless integration of data preprocessing, decomposition, model training, hyperparameter optimization, and evaluation.
Unlike other frameworks, TSPredIT emphasizes the co-optimization of both preprocessing and modeling steps, improving predictive performance.
It supports a variety of statistical and machine learning models, filtering techniques, outlier detection, data augmentation, and ensemble strategies.
More information is available in Salles et al. <doi:10.1007/978-3-662-68014-8_2>.

Eduardo Ogasawara

tspredit

Time Series Prediction with Integrated Tuning

Cristiane Gea

Diego Carvalho

Diogo Santos

Eduardo Bezerra

Esther Pacitti

Fabio Porto

Fernando Alexandrino

Rebecca Salles

Vitoria Birindiba

CEFET/RJ 

do_fit function

<dl><dt>obj</dt>
<dd>Model object to be fitted.</dd>
<dt>x</dt>
<dd>Matrix or data.frame with input features.</dd>
<dt>y</dt>
<dd>Vector or matrix with target values.</dd></dl>

Arguments

Fit Time Series Model — do_fit

<dl>

<dt>obj</dt>
<dd>Model object to be fitted.</dd>


<dt>x</dt>
<dd>Matrix or data.frame with input features.</dd>


<dt>y</dt>
<dd>Vector or matrix with target values.</dd>

</dl>

Fit Time Series Model

do_fit: Fit Time Series Model

Description

Usage

Value

Arguments