Improving Classification Accuracy of Automated Text Classifiers : Basics Concepts, Methods, and Practical Application

Language: English

Published by LAP LAMBERT Academic Publishing, 2019

6200282323 / 9786200282323

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - The number of textual documents are increasing at an incredible rate and very often, there is a need to classify those documents into some fixed predefined categories. The concepts of text mining and machine learning help a lot in this task of automated document classification. Since the classification is being done automatically, the classifier needs to be a good classifier so that there are as less misclassifications as possible. Therefore, the classification accuracy is very important and needs to be taken care of. There are various factors that can affect the classification accuracy of classifiers. One of the factors is the Feature Selection method used to reduce the number of features in the documents. Information Gain (IG) is one of the most popular methods employed for this task but there are few shortcomings in this method of evaluating the better words. In our work, we have devised a new formula for evaluating the words in the documents and thus finding the better words which are more useful in the classification task. Our method aims to find those words which have more discriminating power than others and therefore, we have named our formula as Discriminating Power (DP).…

Seller Inventory # 9786200282323

Title
Improving Classification Accuracy of Automated Text Classifiers : Basics Concepts, Methods, and Practical Application
Author
Shivam Rastogi
Publisher
LAP LAMBERT Academic Publishing
Publication year
2019
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6200282323
ISBN 13
9786200282323
Item weight
96 grams
Dimensions
220x150x4 mm

AHA-BUCH GmbH

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