<p>This constitute simulation of three large data sets in the order of; 10,000×50, 30,000×50 and 50,000×50 dimension. The range of K used is 10≤K≤40 for the four algorithms.</p
<p>Performance comparison of many metrics, including ARI, CSR, , NMI, JI, SI, CH, MML, for all algor...
<p>Comparison of prediction accuracy on four multiclass classification datasets by varying the numbe...
<p>Performance comparison of many metrics, including ARI, CSR, , NMI, JI, SI, CH, MML, for all algor...
(A) The clustering runtime vs. the number of cells in the simulated datasets for all four methods. (...
The k-means algorithm is a widely used clustering tech-nique. Here we will examine the performance o...
Population size = 100 and Generation = 300. (a) Range, (b) Average Tolerance, (c) Average Hamming Di...
The aim of this work is to compare different strategies to cluster large data sets. In particular, t...
Due to current data collection technology, our ability to gather data has surpassed our ability to a...
<p>Computation Time in the stages of: (a) scaled down data clustering, (b) extend to all data cluste...
Accuracy of Algorithm 1 on the synthetic datasets (left) and the KC dataset (right). Each line denot...
(a) success rate, sr(%) versus population and (b) average execution time, rt(s) versus population fo...
<p>In A) different color lines represent the different likelihood-based algorithms tested for popula...
<p>Performance comparison of many metrics, including CSR, , MML, CH, SI for all algorithms in Leukem...
<p>Performance comparison of the proposed algorithm and 17 existing algorithms using four existing e...
Parallel efficiency comparison in the algorithm in this paper and DP K-means.</p
<p>Performance comparison of many metrics, including ARI, CSR, , NMI, JI, SI, CH, MML, for all algor...
<p>Comparison of prediction accuracy on four multiclass classification datasets by varying the numbe...
<p>Performance comparison of many metrics, including ARI, CSR, , NMI, JI, SI, CH, MML, for all algor...
(A) The clustering runtime vs. the number of cells in the simulated datasets for all four methods. (...
The k-means algorithm is a widely used clustering tech-nique. Here we will examine the performance o...
Population size = 100 and Generation = 300. (a) Range, (b) Average Tolerance, (c) Average Hamming Di...
The aim of this work is to compare different strategies to cluster large data sets. In particular, t...
Due to current data collection technology, our ability to gather data has surpassed our ability to a...
<p>Computation Time in the stages of: (a) scaled down data clustering, (b) extend to all data cluste...
Accuracy of Algorithm 1 on the synthetic datasets (left) and the KC dataset (right). Each line denot...
(a) success rate, sr(%) versus population and (b) average execution time, rt(s) versus population fo...
<p>In A) different color lines represent the different likelihood-based algorithms tested for popula...
<p>Performance comparison of many metrics, including CSR, , MML, CH, SI for all algorithms in Leukem...
<p>Performance comparison of the proposed algorithm and 17 existing algorithms using four existing e...
Parallel efficiency comparison in the algorithm in this paper and DP K-means.</p
<p>Performance comparison of many metrics, including ARI, CSR, , NMI, JI, SI, CH, MML, for all algor...
<p>Comparison of prediction accuracy on four multiclass classification datasets by varying the numbe...
<p>Performance comparison of many metrics, including ARI, CSR, , NMI, JI, SI, CH, MML, for all algor...
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