| 000 | 04606nam a22006135i 4500 | ||
|---|---|---|---|
| 001 | 978-3-030-22475-2 | ||
| 003 | DE-He213 | ||
| 005 | 20220801215541.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 190904s2020 sz | s |||| 0|eng d | ||
| 020 |
_a9783030224752 _9978-3-030-22475-2 |
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| 024 | 7 |
_a10.1007/978-3-030-22475-2 _2doi |
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| 050 | 4 | _aTK5101-5105.9 | |
| 072 | 7 |
_aTJK _2bicssc |
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_aTEC041000 _2bisacsh |
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_aTJK _2thema |
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| 082 | 0 | 4 |
_a621.382 _223 |
| 245 | 1 | 0 |
_aSupervised and Unsupervised Learning for Data Science _h[electronic resource] / _cedited by Michael W. Berry, Azlinah Mohamed, Bee Wah Yap. |
| 250 | _a1st ed. 2020. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2020. |
|
| 300 |
_aVIII, 187 p. 55 illus., 45 illus. in color. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aUnsupervised and Semi-Supervised Learning, _x2522-8498 |
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| 505 | 0 | _aChapter1: A Systematic Review on Supervised & Unsupervised Machine Learning Algorithms for Data Science -- Chapter2: Overview of One-Pass and Discard-After-Learn Concepts for Classification and Clustering in Streaming Environment with Constraints -- Chapter3: Distributed Single-Source Shortest Path Algorithms with Two Dimensional Graph Layout -- Chapter4: Using Non-Negative Tensor Decomposition for Unsupervised Textual Influence Modeling -- Chapter5: Survival Support Vector Machines: A Simulation Study and Its Health-related Application -- Chapter6: Semantic Unsupervised Learning for Word Sense Disambiguation -- Chapter7: Enhanced Tweet Hybrid Recommender System using Unsupervised Topic Modeling and Matrix Factorization based Neural Network -- Chapter8: New Applications of a Supervised Computational Intelligence (CI) Approach: Case Study in Civil Engineering. | |
| 520 | _aThis book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data applications. Case studies and best practices are included along with theoretical models of learning for a comprehensive reference to the field. The book is organized into eight chapters that cover the following topics: discretization, feature extraction and selection, classification, clustering, topic modeling, graph analysis and applications. Practitioners and graduate students can use the volume as an important reference for their current and future research and faculty will find the volume useful for assignments in presenting current approaches to unsupervised and semi-supervised learning in graduate-level seminar courses. The book is based on selected, expanded papers from the Fourth International Conference on Soft Computing in Data Science (2018). Includes new advances in clustering and classification using semi-supervised and unsupervised learning; Address new challenges arising in feature extraction and selection using semi-supervised and unsupervised learning; Features applications from healthcare, engineering, and text/social media mining that exploit techniques from semi-supervised and unsupervised learning. | ||
| 650 | 0 |
_aTelecommunication. _910437 |
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| 650 | 0 |
_aSignal processing. _94052 |
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| 650 | 0 |
_aPattern recognition systems. _93953 |
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| 650 | 0 |
_aArtificial intelligence. _93407 |
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| 650 | 0 |
_aData mining. _93907 |
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| 650 | 1 | 4 |
_aCommunications Engineering, Networks. _931570 |
| 650 | 2 | 4 |
_aSignal, Speech and Image Processing . _931566 |
| 650 | 2 | 4 |
_aAutomated Pattern Recognition. _931568 |
| 650 | 2 | 4 |
_aArtificial Intelligence. _93407 |
| 650 | 2 | 4 |
_aData Mining and Knowledge Discovery. _945058 |
| 700 | 1 |
_aBerry, Michael W. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _945059 |
|
| 700 | 1 |
_aMohamed, Azlinah. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _945060 |
|
| 700 | 1 |
_aYap, Bee Wah. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _945061 |
|
| 710 | 2 |
_aSpringerLink (Online service) _945062 |
|
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030224745 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030224769 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030224776 |
| 830 | 0 |
_aUnsupervised and Semi-Supervised Learning, _x2522-8498 _945063 |
|
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-22475-2 |
| 912 | _aZDB-2-ENG | ||
| 912 | _aZDB-2-SXE | ||
| 942 | _cEBK | ||
| 999 |
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