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Research Paper | Computer Science & Engineering | India | Volume 2 Issue 4, April 2013
Data Mining: Finding Outliers from Different Types of Data using Dissimilarity Data Structure
L. Sunitha | M. BalRaju | J. Sasikiran
Abstract: An Outlier is an extreme value in a data set. Using clustering techniques we can detect outliers. Outlier means values that are far away from any cluster. In this paper we tried to find out outliers from Inter-Scaled Variables, Binary Variables, Categorical and Ordinal Variables by using Dissimilarity Data Structure. All similar objects are grouped and objects which are not belonging into any cluster are considered as outliers.
Keywords: Outlier, Dissimilarity, Cluster, Inter-Scaled, Binary, Categorical
Edition: Volume 2 Issue 4, April 2013,
Pages: 292 - 295
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Student Project, Computer Science & Engineering, India, Volume 11 Issue 6, June 2022
Pages: 1875 - 1880Microclustering with Outlier Detection for DADC
Aswathy Priya M.
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Research Paper, Computer Science & Engineering, India, Volume 12 Issue 6, June 2023
Pages: 1168 - 1174A Machine Learning Approach for the Diagnosis of Chronic Kidney Disease
Divya Pogaku | Sneha Bohra [2]