CRAN/E | mildsvm

mildsvm

Multiple-Instance Learning with Support Vector Machines

Installation

About

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) ; Xiao, Liu, and Hao (2018) doi:10.1109/TNNLS.2017.2766164; Muandet et al. (2012) ; Chu and Keerthi (2007) doi:10.1162/neco.2007.19.3.792; and Andrews et al. (2003) . 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 after obtaining a license.

github.com/skent259/mildsvm
Bug report File report

Key Metrics

Version 0.4.0
R ≥ 3.5.0
Published 2022-07-14 624 days ago
Needs compilation? no
License MIT
License File
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Maintainer

Maintainer

Sean Kent

skent259@gmail.com

Authors

Sean Kent

aut / cre

Yifei Liou

aut

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Depends

R ≥ 3.5.0

Imports

dplyr
e1071
kernlab
magrittr
mvtnorm
pillar
pROC
purrr
rlang
stats
tibble
tidyr
utils

Suggests

covr
gurobi
Matrix
testthat