| 000 | 02460nam a22003858i 4500 | ||
|---|---|---|---|
| 001 | CR9780511975820 | ||
| 003 | UkCbUP | ||
| 005 | 20200124160219.0 | ||
| 006 | m|||||o||d|||||||| | ||
| 007 | cr|||||||||||| | ||
| 008 | 101011s2011||||enk o ||1 0|eng|d | ||
| 020 | _a9780511975820 (ebook) | ||
| 020 | _z9780521875806 (hardback) | ||
| 020 | _z9780521699099 (paperback) | ||
| 040 |
_aUkCbUP _beng _erda _cUkCbUP |
||
| 050 | 0 | 0 |
_aRA409.5 _b.M35 2011 |
| 082 | 0 | 0 |
_a614.285 _222 |
| 100 | 1 |
_aMalley, James D., _eauthor. |
|
| 245 | 1 | 0 |
_aStatistical learning for biomedical data / _cJames D. Malley, Karen G. Malley, Sinisa Pajevic. |
| 264 | 1 |
_aCambridge : _bCambridge University Press, _c2011. |
|
| 300 |
_a1 online resource (xii, 285 pages) : _bdigital, PDF file(s). |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
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| 490 | 1 | _aPractical guides to biostatistics and epidemiology | |
| 500 | _aTitle from publisher's bibliographic system (viewed on 05 Oct 2015). | ||
| 520 | _aThis book is for anyone who has biomedical data and needs to identify variables that predict an outcome, for two-group outcomes such as tumor/not-tumor, survival/death, or response from treatment. Statistical learning machines are ideally suited to these types of prediction problems, especially if the variables being studied may not meet the assumptions of traditional techniques. Learning machines come from the world of probability and computer science but are not yet widely used in biomedical research. This introduction brings learning machine techniques to the biomedical world in an accessible way, explaining the underlying principles in nontechnical language and using extensive examples and figures. The authors connect these new methods to familiar techniques by showing how to use the learning machine models to generate smaller, more easily interpretable traditional models. Coverage includes single decision trees, multiple-tree techniques such as Random Forests™, neural nets, support vector machines, nearest neighbors and boosting. | ||
| 650 | 0 |
_aMedical statistics _xData processing. |
|
| 650 | 0 |
_aBiometry _xData processing. |
|
| 700 | 1 |
_aMalley, Karen G., _eauthor. |
|
| 700 | 1 |
_aPajevic, Sinisa, _eauthor. |
|
| 776 | 0 | 8 |
_iPrint version: _z9780521875806 |
| 830 | 0 | _aPractical guides to biostatistics and epidemiology. | |
| 856 | 4 | 0 | _uhttps://doi.org/10.1017/CBO9780511975820 |
| 999 |
_c516603 _d516601 |
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