[PDF.23pk] Learning to Classify Text Using Support Vector Machines (The Springer International Series in Engineering and Computer Science)

Learning to Classify Text Using Support Vector Machines (The Springer International Series in Engineering and Computer Science)

[PDF.lz23] Learning to Classify Text Using Support Vector Machines (The Springer International Series in Engineering and Computer Science)

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 | #3169257 in Books |  Springer |  2002-04-30 | Original language:English | PDF # 1 |  9.21 x.63 x6.14l,1.03 | File type: PDF | 205 pages

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||5 of 5 people found the following review helpful.| The Gold standard|By S. Purpura|This is a must read for anyone beginning to investigate the analysis of meaning in text using computational methods. I found the initial sections were useful in bringing together my thought on many different aspects of the topic.

Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector Machines presents a new approach to generating text classifiers from examples. The approach combines high performance and efficiency with theoretical understanding and improved robustness. In particular, it is highly effective without greedy heuristic components. The SVM approach is computationally efficient in training and classification, and it comes w...

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