tspredit
Time Series Prediction with Integrated Tuning
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2.767 |
2026-04-09 windows/windows R-4.5 | tspredit_1.2.767.zip |
344.1 KiB |