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Event-related Potential analysis using elastic net logistic regression
엘라스틱 넷 로지스틱 회귀분석을 통한 사건 관련 전위 분석

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Authors
이우종
Advisor
김청택
Major
인문대학 협동과정 인지과학전공
Issue Date
2016-02
Publisher
서울대학교 대학원
Keywords
Elastic netRegularizationEvent-related potentialERPLogistic regression
Description
학위논문 (석사)-- 서울대학교 대학원 : 협동과정 인지과학전공, 2016. 2. 김청택.
Abstract
The objective of the thesis is to explore whether regularization techniques can be
applied to ERP analysis, and which type of regularization is adequate. This thesis
proposes elastic net regularization logistic regression as a good candidate of
data analytic method for Event-Related Potential analysis (ERP). Specifically,
regularization techniques are used to identify latency in ERP. Study 1 tested
whether regularization logistic regression can classify latency using simulated
ERP data. It showed that ridge and lasso could identify latency information. In
study 2, the same analyses were applied to actual ERP data. Ridge regression
can identify latency information wheras lasso cannot.
Language
English
URI
https://hdl.handle.net/10371/131732
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College of Humanities (인문대학)Program in Cognitive Science (협동과정-인지과학전공)Theses (Master's Degree_협동과정-인지과학전공)
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