Robust Data Clustering

Robust clustering techniques are an effective way of clustering data in such a form that effect of outliers on the data clusters is minimized. In this book six data clustering techniques are reviewed and analysed based upon the robust characteristics of clustering. Six data clustering algorithms namely: Fuzzy C-Means (FCM), Possibilistic C-Means (PCM), Possibilistic Fuzzy C-means (PFCM), Credibilistic Fuzzy C-means (CFCM), Noise Clustering (NC) and Density Oriented Fuzzy C-Means (DOFCM) are analysed based upon synthetic noisy data-sets and standard data-sets like DUNN and Bensaid.

Autorentext

Prabhjot Kaur received her B.tech in Electronics and communication engineering From Guru Nanak Dev Engineering College, Ludhiana in 2016. From the same college, She received M.tech degree in 2018. Her major research area is VLSI design.