ScholarWorks@Korea University: RYOO, Hong Seo

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RYOO, Hong Seo (류홍서)

College of Engineering

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Tel 02-3290-3394
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Logical analysis of data:5||Feature Selection:3||Pattern:3||기계학습(Machine Learning):2||분류(Classification):2||최적화(Optimization):2||LAD:2||Supervised learning:2||01 multilinear programming:2||01 linearization:2||Boolean logic:2||데이터 마이닝(Data Mining):2||Support Features:1||General Set Covering:1||microarrays:1||Boolean logical pattern:1||Combinatorial Optimization:1||MacroEconomic Indicators:1||Multilinear programming:1||Goal Programming:1||ShortTerm Demand Forecast:1||Hypercube:1||Pattern generation:1||MILP:1||Maximum prime pattern:1||Maximum spanned pattern:1||classification:1||optimization:1||binary classification:1||global optimization:1||경계병사 근무편성:1||Guard Soldier Scheduling:1||Paretooptimal pattern:1||Rule induction:1||Logical Analysis of Data:1||Bioinformatics:1||Supervised machine learning:1||mixed 01 integer and linear program:1||Classification:1||Star:1||Clique:1||Omics Data:1||oligo probes:1||set covering:1||SARS:1||mixed integer and linear programming:1||Graph:1||Strong prime pattern:1||Strong spanned pattern:1||Surrogate Relaxation:1||AI:1||혼합선형.정수 목표계획법:1||machine learning:1||Knowledge discovery:1||Boolean Logic:1||Facetdefining inequalities:1||Multiobjective Programming:1||Combinatorial optimization:1||목표계획법:1||data mining:1||classification1. Introduction패턴 분류(pattern classification)는 두 개 이상의 집합으로 구성된 데이터에서 각 집합의 차별적인 특성을 발견하고 추출하는 데이터마이닝의 기본적인 문제이다. 패턴 분류는 데이터를 구성하는 집합의 개수에 따라 이진 분류(binary classificati:1||Spherical pattern:1||Multiterm polyhedral relaxation:1||Set Covering Problem:1||Integer Programming:1||Mixed 01 integer and linear programming:1||supervised learning:1||Mixed Linear and Integer Programming:1||

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