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Alan H. . Ed(S): Fielding - Machine Learning Methods for Ecological Applications - 9780412841903 - V9780412841903
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Machine Learning Methods for Ecological Applications

€ 190.94
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Description for Machine Learning Methods for Ecological Applications Hardback. The aim of this text is to introduce machine learning methods to professional ecologists. Topics covered in the text include the identification of species, optimal mate choice, predicting species distributions and modelling landscape features. Editor(s): Fielding, Alan H. Num Pages: 261 pages, biography. BIC Classification: RNC. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 17. Weight in Grams: 576.
It is difficult to become an ecologist withou,t acquiring some breadth~ For example, we are expected to be competent statisticians and taxonomists who appreciate the importance of spatial and temporal processes, whilst recognising the potential offered by techniques such as RAPD. It is, therefore, with some trepidation that we offer a collection of potentially useful methods that will be unfamiliar, and possibly alien, to most ecologists. I don't feel old, but when I was undertaking my postgraduate research our lab calculator was mechanical. There was great excitement in my fmal year when we obtained an unbelievably expensive electronic calculator. Later ... Read more

Product Details

Format
Hardback
Publication date
1999
Publisher
Chapman and Hall United Kingdom
Number of pages
261
Condition
New
Number of Pages
261
Place of Publication
London, United Kingdom
ISBN
9780412841903
SKU
V9780412841903
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

Reviews for Machine Learning Methods for Ecological Applications
`I believe this book is a very useful contribution and an excellent starting point for ecologists who are interested in applying machine learning methods to ecological problems.' Uygar Özesmi in Ecology, 81:9 (2000)

Goodreads reviews for Machine Learning Methods for Ecological Applications


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