The elements of statistical learning : Data mining, inference, and prediction
This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyon...
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| Autor principal: | |
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| Formato: | Livro |
| Idioma: | Undetermined |
| Publicado em: |
New York
Springer
2001
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| Thư viện lưu trữ: | Trung tâm Học liệu Trường Đại học Cần Thơ |
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| Resumo: | This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting |
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