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» A Clustering Algorithm Incorporating Density and Direction
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CIMCA
2008
IEEE
13 years 6 months ago
A Clustering Algorithm Incorporating Density and Direction
This paper analyses the advantages and disadvantages of the K-means algorithm and the DENCLUE algorithm. In order to realise the automation of clustering analysis and eliminate hu...
Yu-Chen Song, Michael J. O'Grady, Gregory M. P. O'...
SDM
2009
SIAM
184views Data Mining» more  SDM 2009»
14 years 2 months ago
DensEst: Density Estimation for Data Mining in High Dimensional Spaces.
Subspace clustering and frequent itemset mining via “stepby-step” algorithms that search the subspace/pattern lattice in a top-down or bottom-up fashion do not scale to large ...
Emmanuel Müller, Ira Assent, Ralph Krieger, S...
BCS
2008
13 years 6 months ago
Fast Estimation of Nonparametric Kernel Density Through PDDP, and its Application in Texture Synthesis
In this work, a new algorithm is proposed for fast estimation of nonparametric multivariate kernel density, based on principal direction divisive partitioning (PDDP) of the data s...
Arnab Sinha, Sumana Gupta
PRL
2007
150views more  PRL 2007»
13 years 4 months ago
A method for initialising the K-means clustering algorithm using kd-trees
We present a method for initialising the K-means clustering algorithm. Our method hinges on the use of a kd-tree to perform a density estimation of the data at various locations. ...
Stephen J. Redmond, Conor Heneghan
IWANN
2009
Springer
13 years 11 months ago
Self Organized Dynamic Tree Neural Network
Cluster analysis is a technique used in a variety of fields. There are currently various algorithms used for grouping elements that are based on different methods including partiti...
Juan Francisco de Paz, Sara Rodríguez, Javi...