A Note on the e ectiveness of the LEAST SQUARES CONSENSUS CLUSTERING
نویسندگان
چکیده
We develop a consensus clustering framework proposed three decades ago in Russia and experimentally demonstrate that our least squares consensus clustering algorithm consistently outperforms several recent consensus clustering methods. keywords: consensus clustering, ensemble clustering, least squares
منابع مشابه
Entropy-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 کاملGlobal least squares solution of matrix equation $sum_{j=1}^s A_jX_jB_j = E$
In this paper, an iterative method is proposed for solving matrix equation $sum_{j=1}^s A_jX_jB_j = E$. This method is based on the global least squares (GL-LSQR) method for solving the linear system of equations with the multiple right hand sides. For applying the GL-LSQR algorithm to solve the above matrix equation, a new linear operator, its adjoint and a new inner product are dened. It is p...
متن کاملProposed Procedure for Estimating the Coefficient of Three-factor Interaction for 2^p 3^m 4^q Factorial Experiments (TECHNICAL NOTE)
Three-factor interaction for the two-level, three-level, and four-level factorial designs was studied. A new technique and formula based on the coefficients of orthogonal polynomial contrast were proposed to calculate the effect of the three-factor interaction The results show that the proposed technique was in agreement with the least squares method. The advantages of the new technique are 1) ...
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 کاملOptimization of Meshless Local Petrov-Galerkin Parameters using Genetic Algorithm for 3D Elasto-static Problems (TECHNICAL NOTE)
A truly Meshless Local Petrov-Galerkin (MLPG) method is developed for solving 3D elasto-static problems. Using the general MLPG concept, this method is derived through the local weak forms of the equilibrium equations, by using a test function, namely, the Heaviside step function. The Moving Least Squares (MLS) are chosen to construct the shape functions. The penalty approach is used to impose ...
متن کامل