boostKCP – Boosting k-means Clustering for the Pearson correlation distance

boostKCP

:: DESCRIPTION

boostKCP is a simple but powerful heuristic method for accelerating k-means clustering of large-scale data in life science.

::DEVELOPER

Morishita Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
C++

:: DOWNLOAD

:: MORE INFORMATION

Citation

Ichikawa K, Morishita S.
A Simple but Powerful Heuristic Method for Accelerating k-Means Clustering of Large-Scale Data in Life Science.
IEEE/ACM Trans Comput Biol Bioinform. 2014 Jul-Aug;11(4):681-92. doi: 10.1109/TCBB.2014.2306200. PMID: 26356339.

PWKmeans 1.0 – Penalize & weight K-means Extends the Target Function of K-means

PWKmeans 1.0

:: DESCRIPTION

PWKmeans penalized and weighted K-means extends the target function of K-means.

::DEVELOPER

George C. Tseng

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
C Compiler

:: DOWNLOAD

:: MORE INFORMATION

Citation

George C. Tseng. (2007).
Penalized and weighted K-means for clustering with scattered objects and prior information in high-throughput biological data.
Bioinformatics. 23:2247-2255.

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