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Machine learning and data mining : methods and applications

Machine learning and data mining : methods and applications (6회 대출)

자료유형
단행본
개인저자
Michalski, Ryszard Stanisaw, 1937-. Bratko, Ivan, 1914-. Kubat, Miroslav, 1958-.
서명 / 저자사항
Machine learning and data mining : methods and applications / edited by Ryszard S. Michalski, Ivan Bratko, Miroslav Kubat.
발행사항
Chichester, West Sussex, Eng. ;   New York, NY :   John Wiley Sons,   c1998.  
형태사항
xvi, 456 p. : ill. ; 25 cm.
ISBN
0471971995
서지주기
Includes bibliographical references and index.
일반주제명
Machine learning. Data mining.
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020 ▼a 0471971995
040 ▼a NTE ▼c NTE ▼d IQU ▼d 211009
049 ▼l 111161010
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245 0 0 ▼a Machine learning and data mining : ▼b methods and applications / ▼c edited by Ryszard S. Michalski, Ivan Bratko, Miroslav Kubat.
260 ▼a Chichester, West Sussex, Eng. ; ▼a New York, NY : ▼b John Wiley Sons, ▼c c1998.
300 ▼a xvi, 456 p. : ▼b ill. ; ▼c 25 cm.
504 ▼a Includes bibliographical references and index.
650 0 ▼a Machine learning.
650 0 ▼a Data mining.
700 1 ▼a Michalski, Ryszard Stanisaw, ▼d 1937-.
700 1 ▼a Bratko, Ivan, ▼d 1914-.
700 1 ▼a Kubat, Miroslav, ▼d 1958-.

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 학술정보관(CDL)/B1 국제기구자료실(보존서고8)/ 청구기호 006.31 M149 등록번호 111161010 (6회 대출) 도서상태 분관대출신청 반납예정일 예약 예약가능 R 서비스 M

컨텐츠정보

책소개

Master the new computational tools to get the most out of your information system.

This practical guide, the first to clearly outline the situation for the benefit of engineers and scientists, provides a straightforward introduction to basic machine learning and data mining methods, covering the analysis of numerical, text, and sound data.

New feature

Being able to extract meaningful patterns and strategic knowledge from large stores of information held electronically is increasingly a challenge facing the business and science worlds. In response, methods are being developed for discovering patterns and general rules from the information in databases, data warehouses and document information systems. This book is the first major text dedicated to issues at the intersection of machine learning and data mining - two interrelated fields that provide the foundations for these methods. Written by a team of international experts Machine Learning and Data Mining presents an exciting contribution addressing the new challenge. It provides an introduction to basic methods and its coverage spans the analysis of numerical data, text, images and sound. Most impressively, the book describes applications across a wide spectrum of real world problems, in domains such as engineering, control, biology, medicine and music


정보제공 : Aladin

목차

GENERAL TOPICS.

A Review of Machine Learning Methods (M. Kubat, et al.).

Data Mining and Knowledge Discovery: A Review of Issues and Multistrategy Approach (R. Michalski & K. Kaufman).

Fielded Applications of Machine Learning (P. Langley & H. Simon).

Applications of Inductive Logic Programming (I. Bratko, et al.).

DESIGN AND ENGINEERING.

Application of Machine Learning in Finite Element Computation (B. Dolsak, et al.).

Application of Inductive Learning and Case-Based Reasoning for Troubleshooting Industrial Machines (M. Manago & E. Auriol).

Empirical Assembly Sequence Planning: A Multistrategy Constructive learning Approach (H. Ko).

Inductive Learning in Design: A Method and Case Study Concerning Design of Antifriction Bearing Systems (W. Moczulski).

DETECTION OF PATTERNS IN TEXTS, IMAGES AND MUSIC.

Finding Associations in Collections of Text (R. Feldman & H. Hirsh).

Learning Patterns in Images (R. Michalski, et al.).

Applications of Machine Learning to Music Research: Empirical Investigations into the Phenomenon of Musical Expression (G. Widmer).

COMPUTER SYSTEMS AND CONTROL SYSTEMS.

WebWatcher: A Learning Apprentice for the World Wide Web (R. Armstrong, et al.).

Biologically Inspired Defences Against Computer Viruses (J. Kephart, et al.).

Behavioural Cloning of Control Skill (I. Bratko, et al.).

Acquiring First-order Knowledge About Air Traffic Control (Y. Kodratoff & C. Vrain).

MEDICINE AND BIOLOGY.

Application of Machine Learning to Medical Diagnosis (I. Kononenko, et al.).

Learning to Classify Biomedical Signals (M. Kubat, et al.).

Machine Learning Applications in Biological Classification of River Water Quality (S. Deroski, et al.).

Index.


정보제공 : Aladin

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