توضیحات
Comparison of LEM2 and a Dynamic Reduct Classification Algorithm
Abstract
This thesis presents the results of the implementation and evaluation of two machine learning algorithms [Baz98,GB97] based on notions from Rough Set theory [Paw82]. Both algorithms were implemented and tested using the Weka [WF00] software framework. The main purpose for doing this was to investigate whether the experimental results obtained in [Baz98] could be reproduced,by implementing both algorithms in a framework that provided common functionalities needed by both. As a result of this thesis,a Rough Set framework accompanying the Weka system was designed and implemented,as well as three methods for discretization and three classification methods.
The results of the evaluation did not match those obtained by the original authors. On two standard benchmarking datasets also used previously in [Baz98] (Breast Cancer and Lymphography),significant results indicating that one of the algorithms performed better than the other could not be established,using the Students t-test and a confidence limit of 95%.
However,on two other datasets (Balance Scale and Zoo) differences could be established with more than 95% significance. The “Dynamic Reduct Approach” scored better on the Balance Scale dataset whilst the “LEM2 Approach” scored better on the Zoo dataset.
Keywords: Machine Learning,Rough Sets,LEM2,Dynamic Reducts
Comparison of LEM2 and a Dynamic Reduct Classification Algorithm
a part of Contents
۱ Introduction 1
۱٫۱ Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
۱٫۲ Rationale . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
۱٫۳ Intended audience . . . . . . . . . . . . . . . . . . . . . . . 2
۱٫۴ Structure of this work . . . . . . . . . . . . . . . . . . . . . 3
۱٫۴٫۱ Using the Weka system . . . . . . . . . . . . . . . . 3
۱٫۴٫۲ Embrace and Extend . . . . . . . . . . . . . . . . . . 3
۱٫۵ Structure of this thesis . . . . . . . . . . . . . . . . . . . . . 4
۱٫۶ About the report . . . . . . . . . . . . . . . . . . . . . . . . 5
۲ Machine Learning 7
۲٫۱ Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
۲٫۲ Classification . . . . . . . . . . . . . . . . . . . . . . . . . . 8
۲٫۳ Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
۲٫۴ Restrictions . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
۲٫۵ Common issues . . . . . . . . . . . . . . . . . . . . . . . . . 12
۲٫۶ Taxonomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
۲٫۶٫۱ Why decision rules? . . . . . . . . . . . . . . . . . . 14
۲٫۶٫۲ Why Rough Sets? . . . . . . . . . . . . . . . . . . . 14
۲٫۷ Weka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
۲٫۷٫۱ Manipulating input . . . . . . . . . . . . . . . . . . . 15
۲٫۷٫۲ Representing knowledge . . . . . . . . . . . . . . . . 16
۲٫۷٫۳ Classification algorithms . . . . . . . . . . . . . . . . 16
۲٫۷٫۴ Evaluation methods . . . . . . . . . . . . . . . . . . 18
Comparison of LEM2 and a Dynamic Reduct Classification Algorithm
برای دریافت ترجمه چکیده و فصل اول پایان نامه Comparison of LEM2 and a Dynamic Reduct Classification Algorithm می توانید به فروشگاه اینترنتی محتوای دیجیتال مراجعه کنید یا بر روی عبارت تحقیق در مورد الگوریتم طبقه بندی کاهش دینامیکی کلیک کنید.
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