Package: tspredit 2.0.707

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>.

Authors:Eduardo Ogasawara [aut, ths, cre], Cristiane Gea [aut], Diego Carvalho [ctb], Diogo Santos [aut], Arthur Garcia [aut], Eduardo Bezerra [ctb], Esther Pacitti [ctb], Fabio Porto [ctb], Fernando Alexandrino [aut], Rebecca Salles [aut], Vitoria Birindiba [aut], CEFET/RJ [cph]