Release 0.2.2

Details of the HypertTS update are as follows:

• Adapted to TensorFlow versions 2.11.0 and above.

• Fixed the issue of unstable random seed in NAS mode.

• Fixed handling of int variables in DL mode.

• Updated CI.

• Fixed the unordered indexing problem in the arrow_head data loading.

• Refactored the identification of discrete variables in DL mode.

• Added the Lion optimizer.

• Corrected variable name spelling error, HybirdRNN -> HybridRNN.

• Corrected the trend parameter in the VAR model.

• Adjusted the field of view length for evaluation segmentation in forecast tasks.

• Added seasonal analysis.

• Fixed the issue of truncating negative values to 0 in forecast tasks.

• Updated hypernets and numpy versions.

• Supported the AdamW optimizer (tensorflow >= 2.14.0).

• Adjusted the legend margin in visualizations.

• Add TimeSeriesForestClassifier and IndividualTDEClassifier built-in algorithm for stats mode classification.

• sktime dependencies are removed and replaced with built-in algorithm support. If need to use KNN classification, please manually install sktime.

• Thanks to @NatLee for his contributions to hyperts.