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Ensemble Learning Study and Its Application

Author: ZhangXinDong
Tutor: KangJunJian；LiWenBin
School: Shijiazhuang University of Economics
Course: Applied Computer Technology
Keywords: Integrated learning Information gain Genetic Algorithms Intrusion Detection
CLC: TP181
Type: Master's thesis
Year: 2010
Downloads: 71
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Abstract


Integrated learning (Ensemble Learning) is a machine learning paradigm is one of the current research focus in a number of areas with good . But ensemble learning technology is not yet mature , there are still many problems to be solved in the course of the study , and people look forward to the level of a far cry from the application . The subject of integrated learning in-depth study , on the one hand, the analysis of the pros and cons of the existing methods . On the other hand , the study of the various factors affecting the integrated effect , which pave the way for further improvement of the integrated learning . In the study on the basis of the existing algorithm , propose a new ensemble learning method : for some individual classifier to play a smaller role in the integrated effect or a negative effect on the situation , this paper proposes a classifier selection based on information gain \, this method first constructs the classifier space , and then calculates the individual classifier information gain , the deletion of one or several individual classifier based on information gain , then the final remaining classifier integrated , the experimental results show that after information gain select classifier play a positive role for the data set , not all features are integrated after the integration of superior processing ; this paper presents a method of characteristics based on improved genetic algorithm to select the method of machine learning applied to genetic algorithm, to achieve the purpose of effective selection feature , and then used in the processed data set ensemble learning, experiments show that the set of data processed through this method not only in the integration effect has been greatly improved , but also greatly reduces training time . Finally, the application of integrated learning research, the first detailed analysis of intrusion detection data set ( KDD CUP99 UCI) , . Second, the KDD CUP 99 do the appropriate processing , and then successfully integrated learning approach to this data set . Third , compare the the classic integrated learning method proposed in this paper ensemble learning methods in intrusion detection data set on the effect . In this paper, several experiments and application examples of the proposed new method validation, the results show that the new method is the effectiveness and feasibility .

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory > Automated reasoning,machine learning
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