Document Classification Algorithms
And Feature Selection Techniques with the Practical Test
(Sprache: Englisch)
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...
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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.
Autoren-Porträt von Esraa Hussein, Ahmed Hussein
Hussein, EsraaClassification is one of the most widely used techniques in machine learning. It can be standalone application as in Text Classification or a part from other field as in data mining and text mining. It is the process of classifying the data by predefined groups or classes.
Bibliographische Angaben
- Autoren: Esraa Hussein , Ahmed Hussein
- 2020, 128 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 6200785260
- ISBN-13: 9786200785268
Sprache:
Englisch
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