| 000 | 02472cam a2200409 a 4500 | ||
|---|---|---|---|
| 001 | 17116449 | ||
| 003 | UoK | ||
| 005 | 20180911151305.0 | ||
| 008 | 120111s2012 enka b 001 0 eng | ||
| 010 | _a 2011049968 | ||
| 015 |
_aGBB1D9314 _2bnb |
||
| 016 | 7 |
_a015986169 _2Uk |
|
| 020 | _a9780521190213 (hardback) | ||
| 020 | _a0521190215 (hardback) | ||
| 020 | _a9780521122047 (paperback) | ||
| 020 | _a052112204X (paperback) | ||
| 035 | _a(OCoLC)ocn773533818 | ||
| 040 |
_aDLC _beng _cDLC _dYDX _dBDX _dYDXCP _dCDX _dUKMGB _dOCLCO _dYNK _dOCLCO _dPUL _dDLC |
||
| 042 | _apcc | ||
| 050 | 0 | 0 |
_aQ325.7 _b.M85 2012 |
| 082 | 0 | 0 |
_a006.3/1 _223 |
| 084 |
_aCOM021000 _2bisacsh |
||
| 100 | 1 |
_aMüller, M. E. _q(Martin E.), _d1970- |
|
| 245 | 1 | 0 |
_aRelational knowledge discovery / _cM.E. Müller. |
| 260 |
_aCambridge ; _aNew York : _bCambridge University Press, _c2012. |
||
| 300 |
_avi, 271 p. : _bill. ; _c26 cm. |
||
| 490 | 0 | _aLecture notes on machine learning | |
| 504 | _aIncludes bibliographical references (p. 261-266) and index. | ||
| 520 | _a"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 | _aComputational learning theory. | |
| 650 | 0 | _aMachine learning. | |
| 650 | 0 | _aRelational databases. | |
| 856 | 4 | 2 |
_3Cover image _uhttp://assets.cambridge.org/97805211/90213/cover/9780521190213.jpg |
| 906 |
_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg |
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| 942 |
_2lcc _cLL |
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| 999 |
_c1405 _d1405 |
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