Drift Adaptable Models.

Heimdall

Heimdall is a tool designed for concept drift detection in continuous data streams. When analyzing time series data, it is possible to observe significant changes in the data distribution or in the accuracy of predictive models during the forecasting process. These changes are known as concept drift.

The goal of the Heimdall package is to detect when concept drift occurs, enabling the detection and adaptation of models in non-stationary contexts. The package offers several state-of-the-art methods to identify and handle concept drift, as well as techniques for efficient model adaptation.

Installation

The latest version of Heimdall is available on CRAN:

install.packages("heimdall")

You can install the development version directly from GitHub:

# install.packages("devtools")
library(devtools)
devtools::install_github("cefet-rj-dal/heimdall", force = TRUE, upgrade = "never")

Exemplos

Heimdall usage examples are organized according to drift detection:

• Examples

library(heimdall)
#> Registered S3 method overwritten by 'quantmod':
#>   method            from
#>   as.zoo.data.frame zoo
#> Registered S3 methods overwritten by 'forecast':
#>   method  from 
#>   head.ts stats
#>   tail.ts stats
#> 
#> Attaching package: 'heimdall'
#> The following object is masked from 'package:base':
#> 
#>     norm

Bugs and Feature Requests

If you encounter any issues or would like to suggest new features, please open an issue:

• GitHub Issues.