A Comprehensive Survey on various Feature Selection Methods to Categorize Text Documents
نویسندگان
چکیده
منابع مشابه
An Improved K-Nearest Neighbor with Crow Search Algorithm for Feature Selection in Text Documents Classification
The Internet provides easy access to a kind of library resources. However, classification of documents from a large amount of data is still an issue and demands time and energy to find certain documents. Classification of similar documents in specific classes of data can reduce the time for searching the required data, particularly text documents. This is further facilitated by using Artificial...
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In recent years, production of text documents has seen an exponential growth, which is the reason why their proper classification seems necessary for better access. One of the main problems of classifying text documents is working in high-dimensional feature space. Feature Selection (FS) is one of the ways to reduce the number of text attributes. So, working with a great bulk of the feature spa...
متن کاملA survey on feature selection methods
Feature selection has been the focus of interest for quite some time and much work has been done. It is in demand, in the areas of application for high datasets with tens or hundreds of thousands of variables are available. This survey is a comprehensive overview of many existing methods from the 1970’s to the present. The strengths and weaknesses of different methods are explained and methods ...
متن کاملAn Improved K-Nearest Neighbor with Crow Search Algorithm for Feature Selection in Text Documents Classification
The Internet provides easy access to a kind of library resources. However, classification of documents from a large amount of data is still an issue and demands time and energy to find certain documents. Classification of similar documents in specific classes of data can reduce the time for searching the required data, particularly text documents. This is further facilitated by using Artificial...
متن کاملAn Improved Flower Pollination Algorithm with AdaBoost Algorithm for Feature Selection in Text Documents Classification
In recent years, production of text documents has seen an exponential growth, which is the reason why their proper classification seems necessary for better access. One of the main problems of classifying text documents is working in high-dimensional feature space. Feature Selection (FS) is one of the ways to reduce the number of text attributes. So, working with a great bulk of the feature spa...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2017
ISSN: 0975-8887
DOI: 10.5120/ijca2017913711