Integrated PSO and DE for Data Clustering
نویسندگان
چکیده
منابع مشابه
A Fuzzy C-means Algorithm for Clustering Fuzzy Data and Its Application in Clustering Incomplete Data
The fuzzy c-means clustering algorithm is a useful tool for clustering; but it is convenient only for crisp complete data. In this article, an enhancement of the algorithm is proposed which is suitable for clustering trapezoidal fuzzy data. A linear ranking function is used to define a distance for trapezoidal fuzzy data. Then, as an application, a method based on the proposed algorithm is pres...
متن کاملPSO based Multidimensional Data Clustering: A Survey
Data clustering is considered as one of the most promising data analysis methods in data mining and on the other side KMeans is the well known partitional clustering technique. Nevertheless, K-Means and other partitional clustering techniques struggle with some challenges where dimension is the core concern. The different challenges associated with clustering techniques are preknowledge of init...
متن کاملClustering Multidimensional Data with PSO based Algorithm
Data clustering is a recognized data analysis method in data mining whereas K-Means is the well known partitional clustering method, possessing pleasant features. We observed that, K-Means and other partitional clustering techniques suffer from several limitations such as initial cluster centre selection, preknowledge of number of clusters, dead unit problem, multiple cluster membership and pre...
متن کاملEntropy-based Consensus for Distributed Data Clustering
The increasingly larger scale of available data and the more restrictive concerns on their privacy are some of the challenging aspects of data mining today. In this paper, Entropy-based Consensus on Cluster Centers (EC3) is introduced for clustering in distributed systems with a consideration for confidentiality of data; i.e. it is the negotiations among local cluster centers that are used in t...
متن کاملthe clustering and classification data mining techniques in insurance fraud detection:the case of iranian car insurance
با توجه به گسترش روز افزون تقلب در حوزه بیمه به خصوص در بخش بیمه اتومبیل و تبعات منفی آن برای شرکت های بیمه، به کارگیری روش های مناسب و کارآمد به منظور شناسایی و کشف تقلب در این حوزه امری ضروری است. درک الگوی موجود در داده های مربوط به مطالبات گزارش شده گذشته می تواند در کشف واقعی یا غیرواقعی بودن ادعای خسارت، مفید باشد. یکی از متداول ترین و پرکاربردترین راه های کشف الگوی داده ها استفاده از ر...
ذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Machine Learning and Computing
سال: 2012
ISSN: 2010-3700
DOI: 10.7763/ijmlc.2012.v2.249