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  "Description": "In high-dimensional streaming data analysis, extracting\ncore periodic features under real-time constraints remains\nchallenging. Traditional dimension reduction methods fail to\nadapt to incremental data and yield low accuracy due to\nirrelevant variables. This package provides the Online Sliced\nInverse Regression framework for cosine regression with\nhigh-dimensional irrelevant variables. It integrates subspace\nextraction of sliced inverse regression and incremental\nlearning of online algorithms to efficiently handle periodic\nstreaming data. Cai, Z., Li, R., & Zhu, L. (2020)\n<doi:10.48550/arXiv.2002.02795>.",
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