There are many algorithms that can be used to analyze the database to check the maintenance of all the data sets that are already present. The different types of cluster models include as follows:
- Connectivity models: these are the models that connect one cluster to another cluster. This includes the example of hierarchical clustering that is based on the distance connectivity of one model to another model.
- Centroid models: these are the models that are used to find the clusters using the single mean vector. It includes the example of k-means algorithm.
- Distribution models: it includes the specification of the models that are statistically distributed for example multivariate normal distribution model.
- Density models: deals with the clusters that are densely connected with one another in the regions having the data space.
- Group models: specifies the model that doesn’t provide the refined model for the output and just gives the grouping information