A comparative study of efficient initialization methods for the k ...

We then compare eight commonly used linear time complexity initialization methods on a large and diverse collection of data sets using various performance ...

A Comparative Study of Efficient Initialization Methods for the K ...

Abstract page for arXiv paper 1209.1960: A Comparative Study of Efficient Initialization Methods for the K-Means Clustering Algorithm.

A comparative study of efficient initialization methods for the k-means clustering algorithm. M. Emre Celebi a,*. , Hassan A. Kingravi b, Patricio A. Vela b a ...

A Comparative Study of Efficient Initialization Methods for the K ...

Semantic Scholar extracted view of "A Comparative Study of Efficient Initialization Methods for the K-Means Clustering Algorithm" by M. E. Celebi et al.

A Comparative Study of Efficient Initialization Methods for the K ...

Request PDF | A Comparative Study of Efficient Initialization Methods for the K-Means Clustering Algorithm | K-means is undoubtedly the most ...

A Comparative Study of Efficient Initialization Methods for the K ...

Finally, we analyze the experimental results using non-parametric statistical tests and provide recommendations for practitioners. We demonstrate that popular ...

Celebi, M.E., Kingravi, H.A. and Vela, P.A. (2013) A Comparative ...

Celebi, M.E., Kingravi, H.A. and Vela, P.A. (2013) A Comparative Study of Efficient Initialization Methods for the K-Means Clustering Algorithm. Expert Systems ...

A comparative study of efficient initialization methods for the k ...

Finally, we analyze the experimental results using non-parametric statistical tests and provide recommendations for practitioners. We ...

A Comparative Study of Efficient Initialization Methods for the K ...

Finally, we analyze the experimental results using non-parametric statistical tests and provide recommendations for practitioners. We ...

References - Scientific Research Publishing

Celebi, M.E., Kingravi, H.A. and Vela, P.A. (2013) A Comparative Study of Efficient Initialization Methods for the K-Means Clustering Algorithm.

(PDF) Optimizing K-Means Clustering: A Comparative Study of ...

The research systematically examines a range of optimization techniques, including gradient descent, stochastic gradient descent, and metaheuristic algorithms ...

k-means initialisation algorithms : an extensive comparative study

A Comparative Study of Efficient Initialization Methods for the K-Means Clustering Algorithm · Computer Science, Mathematics. Expert Syst. Appl. · 2013.

An empirical comparison of four initialization methods for the K ...

In addition, we compare the convergence speed of the K-Means algorithm when using each of the four initialization methods. Our results suggest that the Kaufman ...

An Effective Initialization Method Based on Quartiles for the K ...

Objectives: This study aims to speed up the K-means algorithm by offering a deterministic quartile-based seeding strategy for initializing ...

(PDF) A Comparative Study on Number of Clusters Determination ...

A Comparative Study on Number of Clusters Determination and Efficient Centroid Initialization for K-Means Algorithm ... We live in a world were data are generated ...

A Comparative Study on K-Means Clustering and Agglomerative ...

The authors came up with a new KnA method which improves the efficiency of hierarchical ... initialization methods for the k-means clustering algorithm, Expert ...

Initialization of the k-means algorithm A comparison of three methods

“A comparative study of efficient initialization methods for the k-means clustering algorithm”. In: Expert Systems with Applications. 40.1 (2013), pp. 200 ...

AN EFFICIENT INITIALIZATION METHOD FOR K-MEANS ...

Eventually, these spectral signatures are used to initialize the k-means clustering algorithm. The proposed method is implemented on a hyperspectral dataset ...

(PDF) Initialization of cluster refinement algorithms: a review and ...

The results of our experiments illustrate that the random and the Kaufman initialization methods outperform the rest of the compared methods as they make the K- ...

An empirical comparison of four initialization methods for the K ...

A secondary objective is to compare the speedup of the convergence of the K-Means algorithm when using each concrete initialization method (eБciency). In order ...