On the Number of Clusters in Block Clustering Algorithms

For a repeatable response process, data clusters built from noisy data are hollow when the noise amplitude is greater than the dispersion generated by the hidden internal states

B´ ona and Flajolet obtained, in particular, a general statement indicating how local limit theorem can help in evaluating probabilities that two independently chosen random

However, a big data programmer should take care of data distribution when using a computer cluster, otherwise a small data analysis task may overload the system.. Author, F.:

Derquenne [3] provided a method of generating a sample of artificial individuals involving two main steps based on different areas of statistics i.e., sampling, data analysis

On the positive side, we provide a polynomial time algorithm for the decision problem when the schedule length is equal to two, the number of clusters is constant and the number

Estimation of the number of endmembers SU with collaborative sparsity 7 SU chain, using the Hyperspectral Subspace Identification by Minimum Error (HySIME) algorithm [2] for

Though the new algorithm is able to obtain automatically the number of clusters and provides better experimental results, it is still unsuitable for image segmentation since the

A rough analysis sug- gests first to estimate the level sets of the probability density f (Polonik [16], Tsybakov [18], Cadre [3]), and then to evaluate the number of