Outlier Detection using Soft Computing Techniques: Detecting Deviant Objects in Various Information Systems using Soft Computing Methods - Brossura

Sangeetha, T; Amalanathan, Geetha Mary

 
9786207473892: Outlier Detection using Soft Computing Techniques: Detecting Deviant Objects in Various Information Systems using Soft Computing Methods
Brossura
ISBN 10: 6207473892 ISBN 13: 9786207473892
Casa editrice: LAP LAMBERT Academic Publishing, 2024

Sinossi

With the growth of the digital era, data is largely available, so knowledge retrieval from those data is done by data mining algorithms. Among various data mining algorithms, finding outliers is crucial as their occurrence degrades system efficiency. The majority of the research was limited to detecting outliers in a single universe with a single granulation for numerical or categorical data. The existing machine learning outlier detection algorithms work well for quantitative data but they are not directly applied to qualitative, vague and imprecise data which produces ineffective results. There is also ambiguous, uncertain, incomplete, and indeterminate information that persists in this real world. These problems are handled in this research work using rough set theory, intuitionistic fuzzy, and neutrosophic sets. The proposed methodology rough entropy based weighted density outlier detection method has been designed to detect outliers for various information systems. The weighted density value for each object and attribute has been determined to detect outliers. So a true object will never be treated as an outlier.

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Editore
LAP LAMBERT Academic Publishing
Data di pubblicazione
2024
Lingua
Inglese
ISBN 10 
6207473892
ISBN 13 
9786207473892
Rilegatura
Copertina flessibile
Numero di pagine
148
Contatto del produttore
non disponibile
Persona responsabile
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