Name: Outlier Detection using Soft Computing Techniques (en Inglés)
Price: 365.06 PEN
Availability: InStock
Author: Sangeetha, T. ; Amalanathan, Geetha Mary
ISBN: 9786207473892

portada Outlier Detection using Soft Computing Techniques (en Inglés)

Formato

Libro Físico

Autor

T. Sangeetha

Geetha Mary Amalanathan

Editorial

LAP Lambert Academic Publishing

Idioma

Inglés

N° páginas

148

Encuadernación

Tapa Blanda

Dimensiones

22.9 x 15.2 x 0.9 cm

Peso

0.23 kg.

ISBN13

9786207473892

Categorías

Tecnología: cuestiones generales

Outlier Detection using Soft Computing Techniques (en Inglés)

T. Sangeetha (Autor) · Geetha Mary Amalanathan (Autor) · LAP Lambert Academic Publishing · Tapa Blanda

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S/ 365,06

S/ 730,11

Ahorras: S/ 365,06

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Origen: Estados Unidos (Costos de importación incluídos en el precio)

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Reseña del libro "Outlier Detection using Soft Computing Techniques (en Inglés)"

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.