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Neural networks Ensemble for multi-dimensional classification
다중 클래스 분류 문제를 위한 인공신경망 앙상블

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Authors
박상철
Advisor
문병로
Major
공과대학 컴퓨터공학부
Issue Date
2016-02
Publisher
서울대학교 대학원
Keywords
Neural networksEnsembleDivide and conquer
Description
학위논문 (석사)-- 서울대학교 대학원 : 컴퓨터공학부, 2016. 2. 문병로.
Abstract
Artificial neural network (ANN) is devised from human neural system in the field of machine learning. Several techniques including ensemble have been proposed to improve ANN’s performance. In this thesis, we show three types of ensembles for classification task which approaches in the style of divide and conquer: pairwise, hierarchy, helper. The pairwise ensemble is using binary classifiers to solve one classification problem. The hierarchical ensemble is composed of networks which are independently trained to solve each small part of the problem. And the other ensemble method uses a traditional network that is assisted by a helper, trained to solve easy classification that is modified from original classification. The experiments are conducted with the MNIST database and the results show the problem and possibility of the style of divide and conquer in neural network.
Language
English
URI
http://hdl.handle.net/10371/122647
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College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Computer Science and Engineering (컴퓨터공학부)Theses (Master's Degree_컴퓨터공학부)
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