Presentation 2020-10-22
[招待講演]統計的に有意な相互作用探索
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) I will introduce significant pattern mining techniques that are designed to find statistically significant interactions between variables with rigorously controlling false positive rate. Based on Tarone's seminal multiple testing correction method, we can perform significant pattern mining for not only traditional targets such as binary and graph data but continuous data and data with categorical covariates. I will review such recent advances of significant pattern mining.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) pattern mining / statistical significance / variable interaction / multiple testing correction
Paper # IBISML2020-28
Date of Issue 2020-10-13 (IBISML)

Conference Information
Committee IBISML
Conference Date 2020/10/20(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English) Organized Sessions on Frontiers of Machine Learning and General Sessions
Chair Ichiro Takeuchi(Nagoya Inst. of Tech.)
Vice Chair Masashi Sugiyama(Univ. of Tokyo) / Koji Tsuda(Univ. of Tokyo)
Secretary Masashi Sugiyama(AIST) / Koji Tsuda(NTT)
Assistant Atsuyoshi Nakamura(Hokkaido Univ.) / Shigeyuki Oba(Kyoto Univ.)

Paper Information
Registration To Technical Committee on Infomation-Based Induction Sciences and Machine Learning
Language JPN-ONLY
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English)
Sub Title (in English)
Keyword(1) pattern mining
Keyword(2) statistical significance
Keyword(3) variable interaction
Keyword(4) multiple testing correction
1st Author's Name
1st Author's Affiliation *(*)
Date 2020-10-22
Paper # IBISML2020-28
Volume (vol) vol.120
Number (no) IBISML-195
Page pp.pp.47-47(IBISML),
#Pages 1
Date of Issue 2020-10-13 (IBISML)