TSPredIT

TSPredIT (Time Series Prediction with Integrated Tuning) is a framework for time series prediction with automatic preprocessing and hyperparameter optimization. It is built on top of the DAL Toolbox and enhances its capabilities by integrating several advanced functionalities:

• Automatic hyperparameter tuning for models and preprocessing
• Outlier detection and removal
• Time series data augmentation
• Filtering techniques for noise reduction
• Ensemble learning support
• Modular and extensible workflow for predictive modeling

TSPredIT is designed to provide a more flexible and customizable pipeline for building predictive models on time series data, making it easier to compare alternatives and automate repetitive tasks.

Examples

• Data manipulation
• Prediction
• Augmentation
• Filtering

Additional documentation and tutorials for the underlying DAL Toolbox can be found at:

• DAL Toolbox documentation

Installation

The latest version of TSPredIT is available on CRAN:

install.packages("tspredit")

You can install the development version from GitHub:

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

Bug reports and feature requests

To report issues or suggest improvements, please open a ticket here:

https://github.com/cefet-rj-dal/tspredit/issues