Package: mildsvm 0.4.0.9000
mildsvm: Multiple-Instance Learning with Support Vector Machines
Weakly supervised (WS), multiple instance (MI) data lives in numerous interesting applications such as drug discovery, object detection, and tumor prediction on whole slide images. The 'mildsvm' package provides an easy way to learn from this data by training Support Vector Machine (SVM)-based classifiers. It also contains helpful functions for building and printing multiple instance data frames. The core methods from 'mildsvm' come from the following references: Kent and Yu (2022) <arxiv:2206.14704>; Xiao, Liu, and Hao (2018) <doi:10.1109/TNNLS.2017.2766164>; Muandet et al. (2012) <https://proceedings.neurips.cc/paper/2012/file/9bf31c7ff062936a96d3c8bd1f8f2ff3-Paper.pdf>; Chu and Keerthi (2007) <doi:10.1162/neco.2007.19.3.792>; and Andrews et al. (2003) <https://papers.nips.cc/paper/2232-support-vector-machines-for-multiple-instance-learning.pdf>. Many functions use the 'Gurobi' optimization back-end to improve the optimization problem speed; the 'gurobi' R package and associated software can be downloaded from <https://www.gurobi.com> after obtaining a license.
Authors:
mildsvm_0.4.0.9000.tar.gz
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mildsvm.pdf |mildsvm.html✨
mildsvm/json (API)
NEWS
# Install 'mildsvm' in R: |
install.packages('mildsvm', repos = c('https://skent259.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/skent259/mildsvm/issues
- ordmvnorm - Sample ordinal MIL data using mvnorm
distributional-datamultiple-instance-learningordinalsvmweakly-supervised-learning
Last updated 2 years agofrom:b58d05a274. Checks:OK: 1 NOTE: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 22 2024 |
R-4.5-win | NOTE | Oct 22 2024 |
R-4.5-linux | NOTE | Oct 22 2024 |
R-4.4-win | NOTE | Oct 22 2024 |
R-4.4-mac | NOTE | Oct 22 2024 |
R-4.3-win | NOTE | Oct 22 2024 |
R-4.3-mac | NOTE | Oct 22 2024 |
Exports:as_mi_dfas_mild_dfbag_instance_samplingbuild_fmbuild_instance_featureclassify_bagscv_misvmgenerate_mild_dfkfm_exactkfm_nystromkmemimi_dfmildmild_dfmiormismmmisvmmisvm_orovaomisvmsmmsummarize_samplessvor_exc
Dependencies:classclicpp11dplyre1071fansigenericsgluekernlablifecyclemagrittrMASSmvtnormpillarpkgconfigplyrpROCproxypurrrR6Rcpprlangstringistringrtibbletidyrtidyselectutf8vctrswithr