knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "README-" )
License | Linux/osx Build | Windows Build |
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The multiple-instance logistic regression with lasso penalty.
You can install:
install.packages("milr")
install.packages("devtools") devtools::install_github("PingYangChen/milr")
If you encounter a bug, please file a reproducible example on github.
set.seed(100) beta <- runif(5, -5, 5) trainData <- DGP(70, 3, beta) testData <- DGP(30, 3, beta) # default (not use LASSO) milr_result <- milr(trainData$Z, trainData$X, trainData$ID) coef(milr_result) # coefficients fitted(milr_result) # fitted bag labels fitted(milr_result, type = "instance") # fitted instance labels summary(milr_result) # summary milr predict(milr_result, testData$X, testData$ID) # predicted bag labels predict(milr_result, testData$X, testData$ID, type = "instance") # predicted instance labels
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