Classification of Clustering Techniques |
Author(s): |
| Ranjith Kumar. K , Department of Computer Science, Dr.SNS Rajalakshmi college of Arts & Science, Coimbatore ? 641 049, Tamil Nadu, India; M. Praveena, Department of Computer Science, Dr.SNS Rajalakshmi college of Arts & Science, Coimbatore ? 641 049, Tamil Nadu, India |
Keywords: |
| Data Mining, Clustering, Types of Clustering, Classification Clustering Techniques |
Abstract |
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Data mining extract the knowledge from large amount of data which store in multiple heterogeneous databases. The overall goal of the data mining process is to extract information from a large data set and transform it into an understandable form for further use. Clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar to each other than to those in other groups (clusters). Clustering is the one of data mining techniques in which data is divided into the groups of similar objects Clustering is a suitable example of unsupervised classification. The grid based methods use the single uniform grid mesh to partition the entire problem domain into cells. |
Other Details |
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Paper ID: IJSRDV5I70391 Published in: Volume : 5, Issue : 7 Publication Date: 01/10/2017 Page(s): 884-885 |
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