An improved column generation algorithm for minimum sum-of-squares clustering
نویسندگان
چکیده
منابع مشابه
An improved column generation algorithm for minimum sum-of-squares clustering
Given a set of entities associated with points in Euclidean space, minimum sum-of-squares clustering (MSSC) consist in partitioning this set into clusters such that the sum of squared distances from each point to the centroid of its cluster is minimized. A column generation algorithm for MSSC was given in du Merle et al. [15]. The bottleneck of that algorithm is resolution of the auxiliary prob...
متن کاملAn Incremental DC Algorithm for the Minimum Sum-of-Squares Clustering
Here, an algorithm is presented for solving the minimum sum-of-squares clustering problems using their difference of convex representations. The proposed algorithm is based on an incremental approach and applies the well known DC algorithm at each iteration. The proposed algorithm is tested and compared with other clustering algorithms using large real world data sets.
متن کاملAn Incremental DC Algorithm for the Minimum Sum-of-Squares Clustering
Clustering is an unsupervised technique dealing with problems of organizing a collection of patterns into clusters based on similarity. Most clustering algorithms are based on hierarchical and partitional approaches. Algorithms based on an hierarchical approach generate a dendrogram representing the nested grouping of patterns and similarity levels at which groupings change [19]. Partitional cl...
متن کاملAn improved opposition-based Crow Search Algorithm for Data Clustering
Data clustering is an ideal way of working with a huge amount of data and looking for a structure in the dataset. In other words, clustering is the classification of the same data; the similarity among the data in a cluster is maximum and the similarity among the data in the different clusters is minimal. The innovation of this paper is a clustering method based on the Crow Search Algorithm (CS...
متن کاملModified global k-means algorithm for minimum sum-of-squares clustering problems
k-means algorithm and its variations are known to be fast clustering algorithms. However, they are sensitive to the choice of starting points and inefficient for solving clustering problems in large data sets. Recently, a new version of the k-means algorithm, the global k-means algorithm has been developed. It is an incremental algorithm that dynamically adds one cluster center at a time and us...
متن کاملذخیره 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: Mathematical Programming
سال: 2010
ISSN: 0025-5610,1436-4646
DOI: 10.1007/s10107-010-0349-7