Binary Priority Outlier Classifier Based Outlier Elimination

Outliers are records that deviate from normal behavioral pattern. This causes a serious issue when it comes to analysing data. In the recent years there has been great research to identify these outliers. Identifying them not only helps improve analysis of data but also provides many applications. T...

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Bibliographic Details
Published inTurkish journal of computer and mathematics education Vol. 12; no. 3; pp. 4261 - 4266
Main Authors Tushar, Deoras Tejas, Senthilnathan, P, Deeba, K, Kumar, N Venkata Vinod
Format Journal Article
LanguageEnglish
Published Trabzon Karadeniz Technical University Distance Education Research and Application Center 11.04.2021
Subjects
Algorithms
Artificial intelligence
Capital losses
Classification
Classifiers
Computer engineering
Computer science
Data analysis
Datasets
Logic programming
Machine learning
Outliers (statistics)
Pattern analysis
Wireless networks
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Summary:Outliers are records that deviate from normal behavioral pattern. This causes a serious issue when it comes to analysing data. In the recent years there has been great research to identify these outliers. Identifying them not only helps improve analysis of data but also provides many applications. The paper presents a way of indenting these outliers based on priority assigned to the attributes. The priorities are then added for each record in the dataset and the pattern is analysed. A concept based on interquartile range is used to eliminate the outliers. Hence the classifier divides the dataset into two classes: outliers and normal data.
ISSN:1309-4653
1309-4653
DOI:10.17762/turcomat.v12i3.1717