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mlr-org

mlr3verse:Easily Install and Load the 'mlr3' Package Family

The 'mlr3' package family is a set of packages for machine-learning purposes built in a modular fashion. This wrapper package is aimed to simplify the installation and loading of the core 'mlr3' packages. Get more information about the 'mlr3' project at <https://mlr3book.mlr-org.com/>.

Maintained by Marc Becker. Last updated 2 months ago.

machine-learningmetamlr3

55 stars 8.32 score 720 scripts 1 dependents

cran

BioM2:Biologically Explainable Machine Learning Framework

Biologically Explainable Machine Learning Framework for Phenotype Prediction using omics data described in Chen and Schwarz (2017) <doi:10.48550/arXiv.1712.00336>.Identifying reproducible and interpretable biological patterns from high-dimensional omics data is a critical factor in understanding the risk mechanism of complex disease. As such, explainable machine learning can offer biological insight in addition to personalized risk scoring.In this process, a feature space of biological pathways will be generated, and the feature space can also be subsequently analyzed using WGCNA (Described in Horvath and Zhang (2005) <doi:10.2202/1544-6115.1128> and Langfelder and Horvath (2008) <doi:10.1186/1471-2105-9-559> ) methods.

Maintained by Shunjie Zhang. Last updated 1 months ago.

2.54 score

pigian

sense:Automatic Stacked Ensemble for Regression Tasks

Stacked ensemble for regression tasks based on 'mlr3' framework with a pipeline for preprocessing numeric and factor features and hyper-parameter tuning using grid or random search.

Maintained by Giancarlo Vercellino. Last updated 9 months ago.

1.78 score

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