Clustering-
Clustering is a group of of known object but the class name is unknown. In cluster the group of object are created one cluster. In that the class name is not defined because of that clustering also called as unsupervised classification. There is no predefined classes are presented in clustering. The lots of abstract object are collected in clustering and making a group of that object for predict the future outcomes.
Example- In biology the clustering are used for deriving a plant formation and their types with their object name like color,size etc. In clustering lots of objects are define the format but making a group of similar object characteristics and gives a proper name for that cluster.
Applications of Cluster Analysis-
- Market Research.
- Pattern Recognition.
- Data Analysis and Image Processing.
- It is also used for discover the distinct proof of customer as compared their purchasing patterns.
- Clustering also used in biological field and also used in banking sector for detect credit card frauds.
Characteristics of Clustering-
- Scalability
- Ability to deal with different kind of attributes
- High dimensional
- Data ability to deal with noisy data interoperability
Clustering methods-
- Partitioning method
- Hierarchical method
- Density based method
- Grid based method
- Model based method
- Rules-based methods