We present polynomial upper and lower bounds on the number of iterations per- formed by the k -means method (a.k.a. Lloyd’s method) for k -means clustering.. Our upper bounds

Suppose there are m factories called origins or sources produce aI (i=1,2……,m) units of products which are to be transported to n destinations with bJ (J=1,2,……,n) unity of

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A modified version of the fast global k -means (fast GKM) clustering method for clustering the gene expression datasets is proposed.. The fast GKM algorithm is

Very little expander flange movement was observed while attaching the new piping. Since this was the desired effect, the monitoring showed a successful outcome. Offset value

In search of our continued interest for the development of eco-friendly synthetic protocols in electrophilic substitution reactions, we have developed present methodology

De Downlight is uit plastiek gemaakt en vermijdt dus elektrische schoks en glasbreuken Geen onderhoudskosten tijdens de hele

Keywords- Wireless Sensor Network, K-means clustering method, Dynamic Network, distance functions, clustering, Euclidean

A theory-based framework for strategic global human resource staffing policies and practices International. Journal of Human Resource Management ,

The experimental results presented show that the ns- bounding scheme makes exact k-means algorithms faster, and that our Exponion algorithm is significantly faster than

Fuzzy c means is compared with k means for image segmentation, in which Fuzzy c means gives higher accuracy than k means, Gabor Texture Extraction method is used to

Lemma 2.1 yields an upper bound on the number of iterations that k-means needs: Since there are only few points close to hyperplanes, eventually a point switches from one cluster

As the results showed average adjusted of posttest of components of time horizon after excluding the effect of pre-test time horizon in divorced women of the experimental group

To analyze the accuracy of X-Means algorithm in comparison with other clustering algorithms like K-means fast and K-Medoids it is necessary to identify the number of

Once the employer mandate provision becomes effective, a large employer will be subject to a penalty if any of its full-time employees receives a premium tax credit or

For different network sizes, the k-means++ method is generating the initial centroids, then the HACO using k-means is implemented at different centroids to choose the best

The proposed method is a hybrid technique based on parallel K-Means and parallel DBSCAN that combines the benefits of both parallel K-Means and parallel

In the proposed method, finding an optimum „k‟ value is performed by Elbow method and clustering is done by k-means algorithm, hence routing protocol LEACH which