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Principles of data mining

Principles of data mining (1회 대출)

자료유형
단행본
개인저자
Bramer, M. A. (Max A.) , 1948-.
서명 / 저자사항
Principles of data mining / Max Bramer.
발행사항
London :   Springer ,   c2007.  
형태사항
x, 343 p. : ill. ; 24 cm.
총서사항
Undergraduate topics in computer science , 1863-7310
ISBN
9781846287657 (pbk.) 1846287650 (pbk.) :
서지주기
Includes bibliographical references (p. [255]-256) and index.
일반주제명
Data mining.
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245 1 0 ▼a Principles of data mining / ▼c Max Bramer.
260 ▼a London : ▼b Springer , ▼c c2007.
300 ▼a x, 343 p. : ▼b ill. ; ▼c 24 cm.
440 0 ▼a Undergraduate topics in computer science , ▼x 1863-7310
504 ▼a Includes bibliographical references (p. [255]-256) and index.
650 0 ▼a Data mining.

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 세종학술정보원/과학기술실/ 청구기호 006.312 B815p 등록번호 151243968 도서상태 대출가능 반납예정일 예약 서비스 C

컨텐츠정보

목차

Introduction to Data Mining.- Data for Data Mining.- Introduction to Classification: Naive Bayes and Nearest Neighbour.- Using Decision Trees for Classification.- Decision Tree Induction: Using Entropy for Attribute Selection.- Decision Tree Induction: Using Frequency Tables for Attribute Selection.- Estimating the Predictive Accuracy of a Classifier.- Continuous Attributes.- Avoiding Overfitting of Decision Trees.- More about Entropy.- Inducing Modular Rules for Classification.- Measuring the Performance of a Classifier.- Association Rule Mining I.- Association Rule Mining II.- Clustering.- Text Mining.- References.- Appendix A: Essential Mathematics.- Appendix B: Datasets.- Appendix C: Sources of Further Information.- Appendix D: Glossary and Notation.- Appendix E: Solutions to Self-assessment Exercises.- Index.


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