Now showing items 1-4 of 4

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      A dynamic linkage clustering using KD-tree.

      Abudalfa, Shadi; Mikki, Mohammad (2013)
      Some clustering algorithms calculate connectivity of each data point to its cluster by depending on density reachability. These algorithms can find arbitrarily shaped clusters, but they require parameters that are mostly ...
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      BH-centroids: A New Efficient Clustering Algorithm

      Elfarra, Belal K; EL Khateeb, Tayseer J; Ashour, Wesam M. (Science and Engineering Research Support Society, 2013)
      The k-means algorithm is one of most widely used method for discovering clusters in data; however one of the main disadvantages to k-means is the fact that you must specify the number of clusters as an input to the algorithm. ...
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      Clustering Using Optimized Gaussian Kernel Function

      El-Bhissy, Kanaan; El-Faleet, Fadi; Ashour, Wesam M. (SERSC, 2014)
      Clustering and segmentation algorithms that depend on Gaussian kernel function as a way for constructing affinity matrix, these algorithms like spectral clustering algorithms suffer from the poor estimation of parzen window ...
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      K-means algorithm with a novel distance measure

      Abudalfa, Shadi; Mikki, Mohammad (The Scientific and Technological Research Council of Turkey, 2013)
      In this paper, we describe an essential problem in data clustering and present some solutions for it. We investigated using distance measures other than Euclidean type for improving the performance of clustering. We also ...