Conventional clustering means classifying the given data objects as exclusive subsets (clusters).That means we can discriminate clearly whether an object belongs to a cluster or not. However such a partition is insufficient to represent many real situations. Therefore a fuzzy clustering method is offered to construct clusters with uncertain boundaries and allows that one object belongs to overl...

Constrained clustering received a lot of attention in the last years. However, the widely used pairwise constraints are not generally applicable for hierarchical clustering, where the goal is to derive a cluster hierarchy instead of a flat partition. Therefore, we propose for the hierarchical setting—based on the ideas of pairwise constraints—the use of must-link-before (MLB) constraints. In th...

Abstract— Clustering is a powerful technique of data mining for extracting useful information from a set of data and classifies the data into several clusters based on similarity of the pattern. This paper presents the quality estimation for students’ projects data based on hierarchical clustering and fuzzy clustering using Min-Max method. From the experimental results it is seen the fuzzy clus...

A formal framework for the treatment of hierarchical coalition formation and hierarchical agreements under both the bargaining and blocking approaches to coalition formation is introduced, and some first positive results on the possibility of full agreement and the efficiency of hierarchical agreements in face of externalities are given. In particular, it is shown that the possibility of hierar...

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ions for Community-Based Administration

In this work, a hierarchical ensemble of projected clustering algorithm for high-dimensional data is proposed. The basic concept of the algorithm is based on the active learning method (ALM) which is a fuzzy learning scheme, inspired by some behavioral features of human brain functionality. High-dimensional unsupervised active learning method (HUALM) is a clustering algorithm which blurs the da...

one of the most important issues in urban planning is developing sustainable public transportation. the basic condition for this purpose is analyzing current condition especially based on data. data mining is a set of new techniques that are beyond statistical data analyzing. clustering techniques is a subset of it that one of it’s techniques used for analyzing passengers’ trip. the result of t...