| 000 | 03097cam a2200577Ii 4500 | ||
|---|---|---|---|
| 001 | 9780429027192 | ||
| 003 | FlBoTFG | ||
| 005 | 20220509193121.0 | ||
| 006 | m d | ||
| 007 | cr ||||||||||| | ||
| 008 | 201116t20212021flua ob 001 0 eng d | ||
| 040 |
_aOCoLC-P _beng _erda _epn _cOCoLC-P |
||
| 020 |
_a9780429648731 _qelectronic publication |
||
| 020 |
_a0429648731 _qelectronic publication |
||
| 020 |
_a9780429651373 _qelectronic book |
||
| 020 |
_a0429651376 _qelectronic book |
||
| 020 |
_a9780429027192 _qelectronic book |
||
| 020 |
_a0429027192 _qelectronic book |
||
| 020 |
_a9780429646096 _q(electronic bk. : Mobipocket) |
||
| 020 |
_a0429646097 _q(electronic bk. : Mobipocket) |
||
| 020 |
_z9780367135591 _qhardcover |
||
| 024 | 7 |
_a10.1201/9780429027192 _2doi |
|
| 035 | _a(OCoLC)1233304562 | ||
| 035 | _a(OCoLC-P)1233304562 | ||
| 050 | 4 |
_aQA401 _b.B54 2021 |
|
| 072 | 7 |
_aBUS _x061000 _2bisacsh |
|
| 072 | 7 |
_aCOM _x004000 _2bisacsh |
|
| 072 | 7 |
_aCOM _x016000 _2bisacsh |
|
| 072 | 7 |
_aPBT _2bicssc |
|
| 082 | 0 | 4 |
_a511/.8 _223 |
| 100 | 1 |
_aBiecek, Przemyslaw, _eauthor. |
|
| 245 | 1 | 0 |
_aExplanatory model analysis : _bexplore, explain, and examine predictive models / _cPrzemyslaw Biecek, Tomasz Burzykowski. |
| 250 | _aFirst edition. | ||
| 264 | 1 |
_aBoca Raton : _bCRC Press, _c2021. |
|
| 264 | 4 | _c©2021 | |
| 300 | _a1 online resource (xiii, 311 pages). | ||
| 336 |
_atext _2rdacontent |
||
| 337 |
_acomputer _2rdamedia |
||
| 338 |
_aonline resource _2rdacarrier |
||
| 490 | 1 | _aChapman & Hall/CRC data science series | |
| 500 | _a"A Chapman & Hall Book" -- title page. | ||
| 500 | _a1. Introduction. -- 2. Prediction Understanding. -- 3. Model Understanding. -- 4. Model Fidelity. -- 5. Other Topics. | ||
| 520 | _aExplanatory Model Analysis Explore, Explain and Examine Predictive Models is a set of methods and tools designed to build better predictive models and to monitor their behaviour in a changing environment. Today, the true bottleneck in predictive modelling is neither the lack of data, nor the lack of computational power, nor inadequate algorithms, nor the lack of flexible models. It is the lack of tools for model exploration (extraction of relationships learned by the model), model explanation (understanding the key factors influencing model decisions) and model examination (identification of model weaknesses and evaluation of model's performance). This book presents a collection of model agnostic methods that may be used for any black-box model together with real-world applications to classification and regression problems. | ||
| 588 | _aOCLC-licensed vendor bibliographic record. | ||
| 650 | 0 | _aMathematical models. | |
| 650 | 7 |
_aBUSINESS & ECONOMICS / Statistics _2bisacsh |
|
| 650 | 7 |
_aCOMPUTERS / Artificial Intelligence _2bisacsh |
|
| 650 | 7 |
_aCOMPUTERS / Computer Vision & Pattern Recognition _2bisacsh |
|
| 700 | 1 |
_aBurzykowski, Tomasz, _eauthor. |
|
| 856 | 4 | 0 |
_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9780429027192 |
| 856 | 4 | 2 |
_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf |
| 999 |
_c130238 _d130238 |
||