Tag: High-dimensional Data

GeneRave 3.0.9 – Fitting Sparse Response Models to very high Dimensional data

GeneRave 3.0.9

:: DESCRIPTION

GeneRave is an R package designed for fitting sparse response models to very high dimensional data.

::DEVELOPER

CSIRO Transformational Bioinformatics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • R

:: DOWNLOAD

GeneRave

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2008 Apr 15;9:195. doi: 10.1186/1471-2105-9-195.
A general approach to simultaneous model fitting and variable elimination in response models for biological data with many more variables than observations.
Kiiveri HT.

SMK 2011v4 – Mining Low-support Discriminative Patterns from Dense and High-dimensional Data

SMK 2011v4

:: DESCRIPTION

SMK (SupMaxK , a family of anti-monotonic measures) aims at the efficient discovery of discriminative patterns from biological data with high density and high dimensionality (e.g. Gene Expression data, and SNP data), and especially for the discovery of those patterns with relatively low-support but high discriminative power (e.g. odds ratio, information gain, p-value etc), which complements existing discriminative pattern mining algorithms.

::DEVELOPER

Data mining for biomedical informatics at the UMN

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Matlab

:: DOWNLOAD

 SMK

:: MORE INFORMATION

Citation

Gang Fang, Gaurav Pandey, Wen Wang, Manish Gupta, Michael Steinbach and Vipin Kumar
Mining Low-Support Discriminative Patterns from Dense and High-Dimensional Data
IEEE Transaction on Knowledge and Data Engineering (TKDE).2012 (vol. 24 no. 2)pp. 279-294