Abstract. We obtain a class of parametric oscillation modes that we call K-modes with damping and absorption that are connected to the classical harmonic oscillator modes through the “supersymmetric” one-dimensional matrix procedure similar to relationships of the same type between Dirac and Schrödinger equations in particle physics. When a single coupling parameter, denoted by K, is used, it c...

K-Modes is an extension of K-Means clustering algorithm, developed to cluster the categorical data, where the mean is replaced by the mode. The similarity measure proposed by Huang is the simple matching or mismatching measure. Weight of attribute values contribute much in clustering; thus in this paper we propose a new weighted dissimilarity measure for K-Modes, based on the ratio of frequency...

Abstract: This paper introduces three generalized geometric distributions: the binomial, negative binomial and Poisson distribution of the same order k. The generating functions and probability distributions of them are investigated, and then the corresponding modes of the distributions are discussed. By the Fibonacci sequence, the modes of the negative binomial distribution of order k are deri...

Clustering accuracy of partitional clustering algorithm for categorical data depends primarily on the choice of initial data points to instigate the clustering process and hence the clustering results cannot be generated and repeated consistently. In this paper we present an approach to compute initial modes for K-mode partitional clustering algorithm to cluster categorical data sets. Here we u...

Tree automata have been defined to accept trees. Different types of acceptance like bottom-up, top-down, tree walking have been considered in the literature. In this paper, we consider bottom-up tree automata and discuss the sequential distributed version of this model. Generally, this type of distribution is called cooperative distributed automata or the blackboard model. We define the traditi...

The k-modes clustering algorithm has been widely used to cluster categorical data. In this paper, we firstly analyzed the k-modes algorithm and its dissimilarity measure. Based on this, we then proposed a novel dissimilarity measure, which is named as GRD. GRD considers not only the relationships between the object and all cluster modes but also the differences of different attributes. Finally ...