KODAMA
Knowledge Discovery by Accuracy Maximization
An unsupervised and semi-supervised learning algorithm that performs feature extraction from noisy and high-dimensional data. It facilitates identification of patterns representing underlying groups on all samples in a data set. Based on Cacciatore S, Tenori L, Luchinat C, Bennett PR, MacIntyre DA. (2017) Bioinformatics doi:10.1093/bioinformatics/btw705 and Cacciatore S, Luchinat C, Tenori L. (2014) Proc Natl Acad Sci USA doi:10.1073/pnas.1220873111.
- Version2.4.1
- R version≥ 2.10.0 stats,
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Bioinformatics
- Proc Natl Acad Sci USA
- Last release11/05/2024
Documentation
Team
Stefano Cacciatore
Leonardo Tenori
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- Depends3 packages
- Imports1 package
- Suggests3 packages
- Linking To2 packages
- Reverse Depends1 package