What is Cluster Analysis??? - Cluster Analysis or Clustering is a collection of statistical methods, which identifies groups of samples that behave similarly or show similar characteristics. To a layman it could be called as "Look alike groups".
Different Types of Clustering- There are various different types of clustering but the three most prominently used types of clustering are 1. K- Means 2. Agglomerative Hierarchical Clustering 3. DBSCAN
What is K- Means Clustering??? - K- Means Clustering is a method of Data mining which aims to divide population (n observations) into k clusters such that each observation is closest to the cluster with nearest mean. K- Means is useful in subjects like market segmentation, computer vision, agriculture, astronomy etc.
What is Agglomerative Hierarchical Clustering??? - It can be said to be a bottoms up way of clustering where clusters have sub clusters which in turn have sub clusters and so on. All these clusters join together to form one cluster.
What is DBSCAN??? - DBSCAN is a density based clustering which provides partial clustering, in which number of clusters is automatically determined by the algorithm. DBSCAN does not produce a complete clustering since it classifies points in low density area as noise and therefore omits them.
How is Clustering different from Segmentation - Segmentation methods include probability-based grouping of observations and cluster based observations. It includes hierarchical and non-hierarchical methods. Segmentation methods are thus very general category of methodology, which includes clustering methods also.
Applications of Cluster Analysis - Biology, Plant Ecology, Medicinal Imaging, Market Research and Segmentation, Computer Science, Climatology etc. Cluster analysis can be used in all the above mentioned areas in various different ways.
en.wikipedia.org
No comments:
Post a Comment