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kurthornik
RWeka:R/Weka Interface
An R interface to Weka (Version 3.9.3). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Package 'RWeka' contains the interface code, the Weka jar is in a separate package 'RWekajars'. For more information on Weka see <https://www.cs.waikato.ac.nz/ml/weka/>.
Maintained by Kurt Hornik. Last updated 2 years ago.
4 stars 8.38 score 1.8k scripts 14 dependents
bioc
Linnorm:Linear model and normality based normalization and transformation method (Linnorm)
Linnorm is an algorithm for normalizing and transforming RNA-seq, single cell RNA-seq, ChIP-seq count data or any large scale count data. It has been independently reviewed by Tian et al. on Nature Methods (https://doi.org/10.1038/s41592-019-0425-8). Linnorm can work with raw count, CPM, RPKM, FPKM and TPM.
Maintained by Shun Hang Yip. Last updated 5 months ago.
immunooncologysequencingchipseqrnaseqdifferentialexpressiongeneexpressiongeneticsnormalizationsoftwaretranscriptionbatcheffectpeakdetectionclusteringnetworksinglecellcpp
6.26 score 61 scripts 5 dependents
bozercavdar
less:Learning with Subset Stacking
"Learning with Subset Stacking" is a supervised learning algorithm that is based on training many local estimators on subsets of a given dataset, and then passing their predictions to a global estimator. You can find the details about LESS in our manuscript at <arXiv:2112.06251>.
Maintained by Burhan Ozer Cavdar. Last updated 3 years ago.
1.70 score 5 scripts