README.Rmd

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output: github_document
---

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knitr::opts_chunk$set(
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# <img src='https://raw.githubusercontent.com/cefet-rj-dal/tspredit/master/inst/logo.png' align='centre' height='125' width='125'/> TSPredIT

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The Time Series Prediction with Integrated Tuning (TSPredIT) is based on DAL Toolbox with integrated hyperparameter optimization combining machine learning and data preprocessing. It also contains time series outliers removal, data augmentation, ensemble models, and a more flexible workflow design for Data Analytics tasks.

## Installation

The latest version of TSPredIT at CRAN is available at:
<https://CRAN.R-project.org/package=tspredit>

You can install the stable version of TSPredIT from CRAN with:

``` r
install.packages("tspredit")
```

You can install the development version of TSPredIT from GitHub [https://github.com/cefet-rj-dal/tspredit](https://github.com/cefet-rj-dal/tspredit) with:

``` r
library(devtools)
devtools::install_github("cefet-rj-dal/tspredit", force=TRUE, upgrade="never")
```

## Examples

The TSPredIT examples are made available at:
<https://nbviewer.org/github/cefet-rj-dal/tspredit/tree/main/examples>

The TSPredIT is built on top of DAL Toolbox. Documentation of DAL Toolbox is made available at:
<https://cefet-rj-dal.github.io/daltoolbox/>



```{r example}
library(tspredit)
```


## Bugs and new features request
<https://github.com/cefet-rj-dal/tspredit/issues>