A nonparametric clustering technique incorporating the concept of similarity based on the sharing of near neighbors is presented. In addition to being an essentially paraliel approach, the computational elegance of the method is such that the scheme is applicable to a wide class of practical problems involving large sample size and high dimensionality. No attempt is made to show how a priori pr...

We introduce a method for unsupervised clustering of images of 3D objects. Our method examines the space of all images and partitions the images into sets that form smooth and parallel surfaces in this space. It further uses sequences of images to obtain more reliable clustering. Finally, since our method relies on a non-Euclidean similarity measure we introduce algebraic techniques for estimat...

Distributional similarity is a useful notion in estimating the probabilities of rare joint events. It has been employed both to cluster events according to their distributions, and to directly compute averages of estimates for distributional neighbors of a target event. Here, we examine the tradeoffs between model size and prediction accuracy for cluster-based and nearest neighbors distribution...

The present study evaluates the psychometric properties of a therapist measure for evaluating the affective communication created between the patient and therapist during the initial stages of treatment. The Affective Communication Questionnaire (ACQ) was administered to a sample of 81 therapists, each rating a single patient, and principal component analysis indicated the measure has coherent ...

This paper presents a cluster validation based document clustering algorithm, which is capable of identifying an important feature subset and the intrinsic value of model order (cluster number). The important feature subset is selected by optimizing a cluster validity criterion subject to some constraint. For achieving model order identification capability, this feature selection procedure is c...

SETTING Recent evidence indicates that human immunodeficiency virus (HIV) and tuberculosis (TB) related stigma act as a key barrier to the utilisation of associated occupational health services by South African health care workers (HCWs). It also highlights a dearth of appropriate tools to measure HIV and TB stigma among HCWs. OBJECTIVE To test four scales measuring different aspects of stigm...

A novel information identification model is proposed to support accurate classification tasks with mixtures of categorical and real-valued attributes. This model combines the advantages of rough set theory and cluster validity method to promote the classification quality to the higher levels. Real-valued attribute values are pre-processed by fuzzy c-means clustering method and then analyzed by ...