This book presents basic ideas of machine learning in a way that is
easy to understand, by providing hands-on practical advice, using
simple examples, and motivating students with discussions of
interesting applications. The main topics include Bayesian
classifiers, nearest-neighbor classifiers, linear and polynomial
classifiers, decision trees, neural networks, and support vector
machines. Later chapters show how to combine these simple tools by
way of “boosting,” how to exploit them in more complicated
domains, and how to deal with diverse advanced practical issues.
One chapter is dedicated to the popular genetic algorithms.
General
| Imprint: |
Springer International Publishing AG
|
| Country of origin: |
Switzerland |
| Release date: |
October 2016 |
| Firstpublished: |
2015 |
| Authors: |
Miroslav Kubat
|
| Dimensions: |
235 x 155 x 16mm (L x W x T) |
| Format: |
Paperback
|
| Pages: |
291 |
| Edition: |
Softcover reprint of the original 1st ed. 2015 |
| ISBN-13: |
978-3-319-34886-5 |
| Categories: |
Books >
Computing & IT >
General
|
| LSN: |
3-319-34886-8 |
| Barcode: |
9783319348865 |
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