v0.16.5

• Improve consistency with sklearn's v1.2, for OneHotEncoder
• add robust scaler for creating layers and clustering
• relatively faster scaling in preprocessing
• Regression-based classifiers (see https://www.researchgate.net/publication/377227280_Regression-based_machine_learning_classifiers)
• DeepMTS (multivariate time series forecasting with deep quasi-random layers): see https://thierrymoudiki.github.io/blog/2024/01/15/python/quasirandomizednn/forecasting/DeepMTS
• AutoML for MTS (multivariate time series forecasting): see https://thierrymoudiki.github.io/blog/2023/10/29/python/quasirandomizednn/MTS-LazyPredict
• AutoML for DeepMTS (multivariate time series forecasting): see https://github.com/Techtonique/nnetsauce/blob/master/nnetsauce/demo/thierrymoudiki_20240106_LazyDeepMTS.ipynb
• Subsample continuous and discrete responses