Cluster Type Methodologies for Grouping Data

In a continuously changing world global economy and a permanent increasingly amount of data is important to use a cluster type methodology to group these data in order to extract relevant information. The two major types of clustering algorithms that are frequently used are characterized as hierarchical and partitioning.These methods are able to detect cluster structures that exist in economic data if algorithms results are validated. A method to validate a clustering algorithm is represented by analyses of empirical datasets.Diverse methodologies are available for different types of data and this paper presents a study over the main cluster type methodologies for grouping data and how to benefit from them in the economic field.