Clustering Algorithm
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Data analysis plays an indispensable role for understanding various phenomena. Cluster analysis, primitive exploration with little or no prior knowledge, consists of research developed across a wide variety of communities. The diversity,... more
Feature selection is one of the issues that have been raised in the discussion of machine learning and statistical identification model. We have provided definitions for feature selection and definitions needed to understand this issue,... more
Abstract: In this paper, a clustering based machine learning algorithm called Clustering Algorithm System (CAS) is introduced. The CAS algorithm is tested to evaluate its performance and find fruitful results. We have been presented some... more
In this paper an efficient method for data clustering is proposed. The proposed algorithm is a modified psFCM, called the pshFCM clustering algorithm that finds better cluster centers for a given data sets as compared to the cluster... more
All clustering methods have to assume some cluster relationship among the data objects that they are applied on. Similarity between a pair of objects can be defined either explicitly or implicitly. In this paper, we introduce a novel... more
We illustrate with two simple examples how interactive evolutionary computation (IEC) can be applied to exploratory data analysis (EDA). IEC is particularly valuable in an EDA context because the objective function is by definite either... more
A Web services-based toolkit for supporting distributed data mining is presented. A workflow engine is provided within the toolkit to enable a user to compose Web services to implement particular point solutions. Three types of Web... more
ABSTRACT In this paper, an approach for profiling email-born phishing activities is proposed. Profiling phishing activities are useful in determining the activity of an individual or a particular group of phishers. By generating profiles,... more