Relational knowledge discovery (Record no. 34289)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01558cam a2200181 a 4500 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9780521190213 (hardback) |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 |
| Item number | MUL/R |
| 100 1# - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Müller, M. E. |
| 245 10 - TITLE STATEMENT | |
| Title | Relational knowledge discovery |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | Cambridge ; |
| -- | New York : |
| Name of publisher | Cambridge University Press, |
| Year of publication | 2012. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | vi, 271 p. : |
| Other physical details | ill. ; |
| 490 0# - SERIES STATEMENT | |
| Series statement | Lecture notes on machine learning |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | "What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual properties of different approaches"-- |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Computational learning theory. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Relational databases. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | BK |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| Withdrawn status | |
| Lost status | |
| Damaged status | |
| Collection code | Home library | Current library | Shelving location | Date acquired | Cost, normal purchase price | Full call number | Accession Number | Koha item type |
|---|---|---|---|---|---|---|---|---|
| Stack | Kannur University Central Library | Kannur University Central Library | Stack | 17/08/2015 | 60.00 | 006.31 MUL/R | 31346 | BK |