• 제목/요약/키워드: one-class problems

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Support Vector Machines을 이용한 다중 클래스 문제 해결 (Solving Multi-class Problem using Support Vector Machines)

  • 고재필
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제32권12호
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    • pp.1260-1270
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    • 2005
  • 최근 기계학습 분야에서 커널머신을 이용한 대표적 학습기로 Support Vector Machines (SVM)이 주목 받고 있다. SVM은 통계적 학습이론에 기반하여 뛰어난 일반화 성능을 보여주며, 다양한 패턴인식 문제에 적용되고 있다. 그러나. SVM은 이진 분류기이므로 일반적인 다중 클래스 문제에 곧바로 적용할 수 없다. SVM을 다중 클래스 문제의 하나인 얼굴인식에 도입하기 위한 방법으로는, One-Per-Class와 All-Pairs가 대표적이다. 상기 두 방법은 다중 클래스 문제를 여러 개의 이진 클래스 문제로 분할하고, 이들을 다시 종합하여 최종 결정을 내리는 출력코딩이라는 일반적인 방법에 속한다. 본 논문에서는 이진 분류기인 SVM의 다중 클래스 분류기 확장 방안으로 출력코딩 방법론을 설명한다. 또한 출력코딩 방법론의 대표적인 이론적 기반인 ECOC(Ewor-Correcting Output Codes)를 근간으로 하는 새로운 출력코딩 방법들을 제안하고, 얼굴인식 실험을 통해 SVM을 기반 분류기로 사용할 경우의, 출력코딩 방법의 특성을 비교$\cdot$분석한다.

아이다부스트(Adaboost)와 원형기반함수를 이용한 다중표적 분류 기법 (Multi-target Classification Method Based on Adaboost and Radial Basis Function)

  • 김재협;장경현;이준행;문영식
    • 전자공학회논문지CI
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    • 제47권3호
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    • pp.22-28
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    • 2010
  • 최근 기계학습 분야에서 커널머신을 이용한 대표적 분류기로 Adaboost가 주목받고 있다. Adaboost는 통계적 학습이론에 기반하여 뛰어난 일반화 성능을 보여주며, 다양한 패턴인식 문제에 적용되고 있다. 그러나, Adaboost는 이진 분류기이므로 다중표적 분류 문제에 곧바로 적용할 수 없다. 일반적으로 다중 분류 문제를 해결하는 기법으로 One-Vs-All 기법과 Pair-Wise 기법이 대표적이다. 이러한 두 기법은 다중 분류 문제를 여러 개의 이진 분류 문제로 분할하고, 이들을 다시 종합하여 최종 결정을 내리는 출력코딩이라는 일반적인 기법으로 실제 시스템 구성에 적합할만한 분류 성능을 보여주지 못하는 경우가 대부분이다. 본 논문에서는 이진 분류기인 Adaboost의 다중 분류 확장 방안으로 원형 기반 함수를 약한 분류기로 이용하는 Adaboost 기반 다중표적 분류 기법을 제안한다.

A Modified Approach to Density-Induced Support Vector Data Description

  • Park, Joo-Young;Kang, Dae-Sung
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제7권1호
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    • pp.1-6
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    • 2007
  • The SVDD (support vector data description) is one of the most well-known one-class support vector learning methods, in which one tries the strategy of utilizing balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. Recently, with the objective of generalizing the SVDD which treats all training data with equal importance, the so-called D-SVDD (density-induced support vector data description) was proposed incorporating the idea that the data in a higher density region are more significant than those in a lower density region. In this paper, we consider the problem of further improving the D-SVDD toward the use of a partial reference set for testing, and propose an LMI (linear matrix inequality)-based optimization approach to solve the improved version of the D-SVDD problems. Our approach utilizes a new class of density-induced distance measures based on the RSDE (reduced set density estimator) along with the LMI-based mathematical formulation in the form of the SDP (semi-definite programming) problems, which can be efficiently solved by interior point methods. The validity of the proposed approach is illustrated via numerical experiments using real data sets.

A study on the image design PBL class that can be used for e-Digital contents production

  • Ahn, In-Soo
    • 한국컴퓨터정보학회논문지
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    • 제23권2호
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    • pp.77-82
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    • 2018
  • In this paper, we propose an improvement plan to increase the learning effect and satisfaction through the PBL - related video design class. PBL To prepare for the Fourth Industrial Revolution era, we must acquire diverse knowledge and skills to discover problems and solve them creatively. Therefore, various learning methods are being studied, and one of them is PBL learning. PBL is a learner-centered education that explores problems that may arise from specific topics other than existing curriculum-based education methods and finds solutions to problems. In this study, two lectures on video design related to video contents and image contents were taught in PBL class, and PBL class problem was analyzed and the improvement plan was studied.

Effects of Problem-Based Learning (PBL) in Fashion Design Classes

  • Park, HyeSook
    • International Journal of Advanced Culture Technology
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    • 제7권4호
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    • pp.222-228
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    • 2019
  • In recent years, in order to enhance the problem-solving skills required by the industrial field, universities have introduced the Problem-Based Learning(PBL) method to solve the problems caused by the lack of creativity, problem solving ability and self-directed learning. This study applied PBL class methods such as 'learning based on individual specific problems', 'self-directed learning', and 'small-group learning of small members' to practical design of fashion design. To do this, I conducted a questionnaire after conducting research based on the PBL module for one semester in a practical class of fashion design major at P University. As a result of the survey, the satisfaction and achievement of the class conducted by PBL learning method was improved than the existing teaching method. As such, if PBL class is used as a way of solving problems through close communication between professors and learners, it is expected to be established as a learner-centered education method that can improve creativity and professionalism.

Fuzzy SVM for Multi-Class Classification

  • 나은영;홍덕헌;황창하
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2003년도 추계학술대회
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    • pp.123-123
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    • 2003
  • More elaborated methods allowing the usage of binary classifiers for the resolution of multi-class classification problems are briefly presented. This way of using FSVC to learn a K-class classification problem consists in choosing the maximum applied to the outputs of K FSVC solving a one-per-class decomposition of the general problem.

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다층퍼셉트론의 출력 노드 수 증가에 의한 성능 향상 (Performance Improvement of Multilayer Perceptrons with Increased Output Nodes)

  • 오상훈
    • 한국콘텐츠학회논문지
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    • 제9권1호
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    • pp.123-130
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    • 2009
  • 일반적으로 다층퍼셉트론을 패턴인식 문제에 적용할 경우 클래스 당 하나의 출력 노드를 배정하고, 이 출력 노드의 인덱스가 입력 패턴의 클래스를 뜻하도록 한다. 이 논문에서는 이와 달리 다층퍼셉트론의 성능 향상을 위하여 클래스 당 출력노드 수를 증가시키는 방법을 제안한다. 두 개의 클래스 문제를 대상으로 클래스 발생확률이 동일하고 각 클래스 내에서 출력노드가 균일분포를 지닌다는 가정 하에, 이 방법의 효용성을 확률론적인 유도를 통하여 증명하였다. 그리고, 50개의 고립단어 인식의 시뮬레이션으로 출력노드를 증가 시킬 경우 성능이 향상됨을 확인하였다.

Analyzing the Problems of Chinese Students Studying at Universities in Korea

  • Eunjoo Oh
    • International Journal of Advanced Culture Technology
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    • 제12권3호
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    • pp.106-113
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    • 2024
  • This study is conducted to determine whether Chinese students currently attending Korean universities are satisfied with their university life and to identify the problems they are experiencing. A survey was conducted with the graduate students attending K University and 202 students participated in the study. According to the study, most students are very satisfied with Korean universities and would recommend them to their friends. Regardless of gender, degree program, or major, the most difficult aspect of school life is understanding and communicating in class due to language problems. Even students with high TOPIK scores experience difficulties in communication and comprehension during class. One of the most significant problems that Chinese students have is a lack of interaction with Korean students. They want to interact with Korean students through club and team activities at the university. They requested that the university provide international students with opportunities to participate in various programs, such as sports activities, to help overcome feelings of alienation and isolation. Based on the study results, suggestions to support Chinese students to adjust educational environments in Korea were presented.

SOLVING A CLASS OF GENERALIZED SEMI-INFINITE PROGRAMMING VIA AUGMENTED LAGRANGIANS

  • Zhang, Haiyan;Liu, Fang;Wang, Changyu
    • Journal of applied mathematics & informatics
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    • 제27권1_2호
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    • pp.365-374
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    • 2009
  • Under certain conditions, we use augmented Lagrangians to transform a class of generalized semi-infinite min-max problems into common semi-infinite min-max problems, with the same set of local and global solutions. We give two conditions for the transformation. One is a necessary and sufficient condition, the other is a sufficient condition which can be verified easily in practice. From the transformation, we obtain a new first-order optimality condition for this class of generalized semi-infinite min-max problems.

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