Classif. of TESS LCs for T Tauri stars

In the testing sample, the algorithm assigns mixed classes to 27% of the stars, reaching up to five simultaneous classes. A catalog of 3672 TTauri star candidates is presented, along with their possible period estimations, predicted morphological classes, and visually revised ones. The cross-validation estimated performance of the final classifiers is reported.

Binary classifiers surpass multiclass recall values for classes with less representation in the training sample. Support vector machines and random forest classifiers obtain better recalls. For comparison, another performance estimation of the final classifiers is calculated using the revised classes of our testing sample, indicating that this performance excels in singled classed stars, which happens in about 75% of the testing sample.