| 000 | 01237nam a2200217 i 4500 | ||
|---|---|---|---|
| 001 | 9789814366175 | ||
| 005 | 20250414083508.0 | ||
| 008 | 240416t2012 xxu e 001 0 eng | ||
| 020 | _a9789814366175 | ||
| 037 |
_bWorld Scientific Publishing _cUSD 137.00 |
||
| 037 | _fBB | ||
| 041 | _aeng | ||
| 072 | 7 |
_aBUS069030 _2bisacsh |
|
| 100 | 1 |
_4A01 _aGilboa, Itzhak |
|
| 245 | 1 | 0 | _aCase-based Predictions: An Axiomatic Approach To Prediction, Classification And Statistical Learning |
| 260 | 2 |
_bWorld Scientific _c2012 |
|
| 520 | _bThe book presents an axiomatic approach to the problems of prediction, classification, and statistical learning. Using methodologies from axiomatic decision theory, and, in particular, the authors' case-based decision theory, the present studies attempt to ask what inductive conclusions can be derived from existing databases. It is shown that simple consistency rules lead to similarity-weighted aggregation, akin to kernel-based methods. It is suggested that the similarity function be estimated from the data. The incorporation of rule-based reasoning is discussed. | ||
| 521 | _aProfessional and scholarly | ||
| 540 |
_aFor sale with non-exclusive rights _bWORLD |
||
| 700 | 1 |
_4A01 _aSchmeidler, David |
|
| 999 |
_c9980 _d9980 |
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