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

Rastogi, Shivam

 
9786200282323: Improving Classification Accuracy of Automated Text Classifiers: Basics Concepts, Methods, and Practical Application
Softcover
ISBN 10: 6200282323 ISBN 13: 9786200282323
Verlag: LAP LAMBERT Academic Publishing, 2019

Inhaltsangabe

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).

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Über die Autorin bzw. den Autor

Shivam Rastogi, currently working as a Software Development Engineer at Amazon India. I studied Master of Technology in Computer Science from Delhi Technological University, Delhi. I have research interests in the fields of Data Mining and Machine Learning, and so I have worked on the Automated Text Classifiers which use these concepts.

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Verlag
LAP LAMBERT Academic Publishing
Erscheinungsdatum
2019
Sprache
Englisch
ISBN 10 
6200282323
ISBN 13 
9786200282323
Einband
Taschenbuch
Anzahl der Seiten
52
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
AV Akademikerverlag
customerservice@vdm-vsg.de

Brivibas gatve 197
Riga
1039
Lettland