MGR: An information theory based hierarchical divisive clustering algorithm for categorical data

نویسندگان

  • Hongwu Qin
  • Xiuqin Ma
  • Tutut Herawan
  • Jasni Mohamad Zain
چکیده

http://dx.doi.org/10.1016/j.knosys.2014.03.013 0950-7051/ 2014 Elsevier B.V. All rights reserved. ⇑ Corresponding author at: Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, Lebuhraya Tun Razak, Gambang, 26300 Kuantan, Malaysia. E-mail addresses: [email protected] (H. Qin), [email protected] (X. Ma), [email protected] (T. Herawan), [email protected] (J.M. Zain). Hongwu Qin , Xiuqin Ma a,b,⇑, Tutut Herawan , Jasni Mohamad Zain a

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

DIVCLUS-T: A monothetic divisive hierarchical clustering method

DIVCLUS-T is a divisive hierarchical clustering algorithm based on a monothetic bipartitional approach allowing the dendrogram of the hierarchy to be read as a decision tree. It is designed for either numerical or categorical data. Like the Ward agglomerative hierarchical clustering algorithm and the k-means partitioning algorithm, it is based on the minimization of the inertia criterion. Howev...

متن کامل

ارائه یک الگوریتم خوشه بندی برای داده های دسته ای با ترکیب معیارها

Clustering is one of the main techniques in data mining. Clustering is a process that classifies data set into groups. In clustering, the data in a cluster are the closest to each other and the data in two different clusters have the most difference. Clustering algorithms are divided into two categories according to the type of data: Clustering algorithms for numerical data and clustering algor...

متن کامل

Holo-Entropy Based Categorical Data Hierarchical Clustering

Clustering high-dimensional data is a challenging task in data mining, and clustering high-dimensional categorical data is even more challenging because it is more difficult to measure the similarity between categorical objects. Most algorithms assume feature independence when computing similarity between data objects, or make use of computationally demanding techniques such as PCA for numerica...

متن کامل

Data Mining Process Using Clustering : A Survey

Clustering is a basic and useful method in understanding and exploring a data set. Clustering is division of data into groups of similar objects. Each group, called cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Interest in clustering has increased recently in new areas of applications including data mining, bioinformatics, web mining...

متن کامل

Modified Convex Data Clustering Algorithm Based on Alternating Direction Method of Multipliers

Knowing the fact that the main weakness of the most standard methods including k-means and hierarchical data clustering is their sensitivity to initialization and trapping to local minima, this paper proposes a modification of convex data clustering  in which there is no need to  be peculiar about how to select initial values. Due to properly converting the task of optimization to an equivalent...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Knowl.-Based Syst.

دوره 67  شماره 

صفحات  -

تاریخ انتشار 2014