| 000 | 02690nam a22003978a 4500 | ||
|---|---|---|---|
| 005 | 20250919005616.0 | ||
| 006 | m|||||o||d|||||||| | ||
| 007 | cr|||||||||||| | ||
| 008 | 151016s2014||||enk s ||1 0|eng|d | ||
| 020 |
_a9781139176224 _qelectronic book _cRM856.05 |
||
| 039 | 9 |
_a201606081035 _basmany _c201601141606 _dhayat _c201601141017 _dlatihan _c201511181628 _dhazriq _y10-16-2015 _zhafiz _wUPO_10044530-hafizupload16102015.mrc _x51 |
|
| 040 |
_aUkCbUP _cUkCbUP _erda |
||
| 090 | _aebookQ325.5.K86 2014 | ||
| 090 |
_aebookQ325.5 _b.K86 2014 |
||
| 100 | 1 |
_aKung, S. Y., _eauthor. |
|
| 245 | 1 | 0 |
_aKernel methods and machine learning / _cS. Y. Kung. |
| 246 | 3 | _aKernel methods & machine learning. | |
| 264 | 1 |
_aCambridge : _bCambridge University Press, _c2014. |
|
| 300 |
_a1 online resource (572 pages) : _bdigital, PDF file(s). |
||
| 336 |
_atext _2rdacontent |
||
| 337 |
_acomputer _2rdamedia |
||
| 338 |
_aonline resource _2rdacarrier |
||
| 500 | _aTitle from publisher's bibliographic system (viewed on 08 Oct 2015). | ||
| 520 | _aOffering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In addition, several other theorems are devoted to proving mathematical equivalence between seemingly unrelated models. With over 25 closed-form and iterative algorithms, the book provides a step-by-step guide to algorithmic procedures and analysing which factors to consider in tackling a given problem, enabling readers to improve specifically designed learning algorithms, build models for new applications and develop efficient techniques suitable for green machine learning technologies. Numerous real-world examples and over 200 problems, several of which are Matlab-based simulation exercises, make this an essential resource for graduate students and professionals in computer science, electrical and biomedical engineering. Solutions to problems are provided online for instructors. | ||
| 650 | 0 | _aSupport vector machines. | |
| 650 | 0 | _aMachine learning. | |
| 650 | 0 | _aKernel functions. | |
| 773 | 0 | _tCambridge Books Online. | |
| 776 | 0 | 8 |
_iPrint version: _z9781107024960. |
| 856 | 4 | 0 | _uhttps://eresourcesptsl.ukm.remotexs.co/user/login?url=http://dx.doi.org/10.1017/CBO9781139176224 |
| 907 |
_a.b16219909 _b2022-10-14 _c2019-11-12 |
||
| 942 |
_c01 _n0 _kebookQ325.5.K86 2014 |
||
| 914 | _avtls003594657 | ||
| 998 |
_ae _b2015-03-10 _cm _dz _feng _genk _y0 _z.b16219909 |
||
| 999 |
_c599693 _d599693 |
||