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{ "item_title" : "Machine Learning for Spatial Environmental Data", "item_author" : [" Mikhail Kanevski", "Alexei Pozdnoukhov", "Vadim Timonin "], "item_description" : "The book presents the state of the art in machine learning algorithms (artificial neural networks of different architectures, support vector machines, etc.) as applied to the classification and mapping of spatially distributed environmental data. Basic geostatistical algorithms are presented as well. New trends in machine learning and their application to spatial data are given, and real case studies based on environmental and pollution data are carried out. The book provides a CD-ROM with the Machine Learning Office software, including sample sets of data, that will allow both students and researchers to put the concepts rapidly to practice.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/0/84/938/237/0849382378_b.jpg", "price_data" : { "retail_price" : "175.00", "online_price" : "175.00", "our_price" : "175.00", "club_price" : "175.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Machine Learning for Spatial Environmental Data|Mikhail Kanevski

Machine Learning for Spatial Environmental Data : Theory, Applications and Software

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Earliest ship date: April 29, 2026
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Overview

The book presents the state of the art in machine learning algorithms (artificial neural networks of different architectures, support vector machines, etc.) as applied to the classification and mapping of spatially distributed environmental data. Basic geostatistical algorithms are presented as well. New trends in machine learning and their application to spatial data are given, and real case studies based on environmental and pollution data are carried out. The book provides a CD-ROM with the Machine Learning Office software, including sample sets of data, that will allow both students and researchers to put the concepts rapidly to practice.

This item is Non-Returnable

Details

  • ISBN-13: 9780849382376
  • ISBN-10: 0849382378
  • Publisher: Epfl Press
  • Publish Date: April 2009
  • Dimensions: 9.6 x 6.6 x 1.1 inches
  • Shipping Weight: 1.85 pounds
  • Page Count: 392

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