Clustering is an unsupervised technique of Data Mining. It means grouping similar objects together and separating the dissimilar ones. Each object in the data set is assigned a class label in the clustering process using a distance measure. This paper has captured the problems that are faced in real when clustering algorithms are implemented .It also considers the most extensively used tools wh...

Clustering is a core problem in data mining and machine learning. It has innumerable applications in many fields. Recently, using the evolutionary algorithms for the clustering problem has become more and more popular. In this paper, we propose an automatic clustering differential evolution (DE) technique for the clustering problem. Our approach can be characterized by (i) proposing a modified ...

AbstructShell clustering algorithms are ideally suited for computer vision tasks such as boundary detection and surface approximation, particularly when the boundaries have jagged or scattered edges and when the range data is sparse. This is because shell clustering is insensitive to local aberrations, it can be performed directly in image space, and unlike traditional approaches it does assume...

background: finding the right word is a necessity in communication, and its evaluation has always been a challenging clinical issue, suggesting the need for valid and reliable measurements. the homophone meaning generation test (hmgt) can measure the ability to switch between verbal concepts, which is required in word retrieval. the purpose of this study was to adapt and validate the persian ve...

The Adjusted Rand Index (ARI) is frequently used in cluster validation since it is a measure of agreement between two partitions: one given by the clustering process and the other defined by external criteria. In this paper we investigate the usability of this clustering validation measure in supervised classification problems by two different approaches: as a performance measure and in feature...

Sequence clustering is one of most fundamental topics which can be applied in various research field. Most of previous work on sequence clustering is dedicated to the single-label clustering in which the whole similarity of equal-length sequence is considered and measured by Euclidean distance function. However, intrinsic properties behind sequence demand the multi-label clustering. In addition...

"Clustering" the significance and application of this technique is spread over various fields. Clustering is an unsupervised process in data mining, that is why the proper evaluation of the results and measuring the compactness and separability of the clusters are important issues. The procedure of evaluating the results of a clustering algorithm is known as cluster validity measure. Different ...

This paper investigates the information in corporate credit ratings from a positive and normative perspective. If ratings are to be informative indicators of credit risk they must reflect what a risk-averse investor cares about: both raw default probability and systematic risk. We find that ratings are inaccurate measures of raw default probability they are dominated as predictors of failure by...

objectives: the aim of this study was to translate the craig hospital inventory of environmental factors (chief) into persian language and to evaluate the validity and reliability of persian version of chief to use for children with cerebral palsy. methods: the chief was translated from english into persian based on the international quality of life assessment (iqola) approach. the persian vers...

OBJECTIVE Although several self-report versions of the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) have been developed and used widely, few psychometric studies have established the construct validity of this measure. Therefore, we developed Korean self-report version of the Y-BOCS and evaluated its factor structure, reliability, and validity. METHODS A non-clinical student sample (n=206) ...