Outlier Detection using Clustering Techniques – K-means and K-median

2020 ◽  
Author(s):  
B. Angelin ◽  
A. Geetha
Keyword(s):  
Outlier Detection ◽  
Clustering Techniques

Clustering Techniques for Outlier Detection

2011 ◽  
pp. 180-183 ◽  
Author(s):  
Frank Klawonn ◽  
Frank Rehm
Keyword(s):  
Knowledge Discovery ◽  
Outlier Detection ◽  
Rare Events ◽  
Knowledge Discovery In Databases ◽  
Clustering Techniques

For many applications in knowledge discovery in databases, finding outliers, which are rare events, is of importance. Outliers are observations that deviate significantly from the rest of the data, so they seem to have been generated by another process (Hawkins, 1980). Such outlier objects often contain information about an untypical behaviour of the system.

scholarly journals Outlier Detection using Clustering Techniques

2018 ◽  
Vol 7 (3.12) ◽  
pp. 813
Author(s):  
Srividya . ◽  
S Mohanavalli ◽  
N Sripriya ◽  
S Poornima
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Outlier Detection ◽  
Heart Diseases ◽  
The Other ◽  
Suitable Method ◽  
Data Sets ◽  
Clustering Techniques

An outlier is nothing but a pattern that is different compared to the other existing  patterns in a particular dataset. In some applications it is very important to understand and identify outliers. Detecting outlier is of major importance in many of the fields like cybersecurity, machine learning, finance, healthcare, etc., A clustering based method is proposed to detect outliers using different algorithms like k means, PAM, Clara, DBScan and LOF on different data sets like breast cancer, heart diseases, multi shaped datasets. This work aims to identify the best suitable method to detect the outliners accurately.   

Clustering techniques for thyroid nodules malignancy inference in the era of personalized medicine

2020 ◽  
Author(s):  
Andrea Giani ◽  
de Souza Patricia Borges ◽  
Stefania Bartoletti ◽  
Flavio Morselli ◽  
Andrea Conti ◽  
...  
Keyword(s):  
Personalized Medicine ◽  
Thyroid Nodules ◽  
Clustering Techniques

Classic Outlier Detection from Web Clusters using Disimilarity Measure

2012 ◽  
Vol 2 (3) ◽  
pp. 98-101 ◽  
Author(s):  
E.Sateesh E.Sateesh ◽  
◽  
M.L.Prasanthi M.L.Prasanthi
Keyword(s):  
Outlier Detection ◽  
Web Clusters
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