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portada Document Classification Algorithms
Type
Physical Book
Language
English
Pages
128
Format
Paperback
Dimensions
22.9x15.2x0.8 cm
Weight
0.20 kg.
ISBN13
9786200785268

Document Classification Algorithms

Esraa Hussein (Author) · Ahmed Hussein (Author) · LAP Lambert Academic Publishing · Paperback

Document Classification Algorithms - Hussein, Esraa ; Hussein, Ahmed

New Book Imported to Taiwan
Delivery: 01 Oct - 09 Oct Shipping: 14 to 15 business days.
NT$ 2,082
NT$ 2,082

Synopsis "Document Classification Algorithms"

Documents classification is one of the most important fields in Natural language processing and text mining. There are many algorithms can be used to perform this task. Most of the used algorithms are from machine learning like: Decision Tree, Support Vector Machine, K-Nearest Neighbors and Naïve Bayes. These are the most essential four classification algorithms. Many researches try to modify and improve these algorithms for text classification. In this book, our work is divided into two levels: (i) a comparative study for these four algorithms, (ii) studying the improvement of document classification with feature selection where four feature selection methods are used and a new feature selection method is suggested.

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