Machine learning for spatial environmental data : theory, applications and software Mikhail Kanevski, Alexei Pozdnoukhov and Vadim Timonin.
Material type:
TextLanguage: English Series: Publication details: New Delhi Wiley india pvt 2014Edition: First editionDescription: xi, 309p.; hbkISBN: - 9788126552023
- 9781439808085 (ebook)
- 006.31 KAN
Contents:
ch. 1. Learning from geospatial data -- ch. 2. Exploratory spatial data analysis : presentation of data and case studies -- ch. 3. Geostatistics -- ch. 4. Artificial neural networks -- ch. 5. Support vector machines and kernel methods.
| Item type | Current library | Call number | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|
Books
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Central Library General Section | 006.31 KAN (Browse shelf(Opens below)) | Available | 029786 |
Browsing Central Library shelves, Shelving location: General Section Close shelf browser (Hides shelf browser)
| 006.3 ALE How to build a mind : | 006.3 COL Artificial Experts | 006.3 WAR Artificial intelligence : | 006.31 KAN Machine learning for spatial environmental data : | 006.31 KUL Elementary Introduction to Station learning Theory | 006.31 SUG Statistical reinforcement learning : | 006.312 HAN Practical data mining |
ch. 1. Learning from geospatial data -- ch. 2. Exploratory spatial data analysis : presentation of data and case studies -- ch. 3. Geostatistics -- ch. 4. Artificial neural networks -- ch. 5. Support vector machines and kernel methods.
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