Document Classification Algorithms

Esraa Hussein

ISBN 10: 6200785260 / ISBN 13: 9786200785268

Published by LAP LAMBERT Academic Publishing Apr 2020, 2020

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch.

Seller Inventory # 9786200785268

Bibliographic Details

• Title: Document Classification Algorithms
• Publisher: LAP LAMBERT Academic Publishing Apr 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 6200785260
• ISBN 13: 9786200785268
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 9D millimeters 220 millimeters width by 150 millimeters height by 9 millimeters depth
• Weight: 209 grams

About this title

Synopsis

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.