Determining Big Data Complexity Using Hierarchical Structure of Groups and Clusters in Decision Tree

This study proposes a new method for determining the degree of big data complexity based on hierarchical structure of all groups and all clusters in big data. The new method for determining the degree of big data complexity uses the tree structure of hierarchical groups and clusters for attributes of big data. The number of groups is always greater than or equal to the number of clusters in big data. The levels and layers of groups and clusters are determined using the tree structure of big data. The grouping level is defined as the last level of leaves in the tree structure. The clustering level is defined as the first level of leaves in the tree structure. The degree of big data complexity is defined as the difference between the grouping level and clustering level. This study defines a new method for (i) determining the degree of big data complexity, (ii) finding the levels and layers of big data complexity and (iii) visualization of big data complexity.