pipeline_ovr
From mlr3pipelines v0.3.0
by Martin Binder
Create A Graph to Perform "One vs. Rest" classification.
Create a new Graph
for a classification Task to
perform "One vs. Rest" classification.
Usage
pipeline_ovr(graph)
Arguments
- graph
Graph
Graph being wrapped betweenPipeOpOVRSplit
andPipeOpOVRUnite
. The Graph should returnNULL
during training and a classification Prediction during prediction.
Value
Examples
# NOT RUN {
library("mlr3")
task = tsk("wine")
learner = lrn("classif.rpart")
learner$predict_type = "prob"
# Simple OVR
g1 = pipeline_ovr(learner)
g1$train(task)
g1$predict(task)
# Bagged Learners
gr = po("replicate", reps = 3) %>>%
po("subsample") %>>%
learner %>>%
po("classifavg", collect_multiplicity = TRUE)
g2 = pipeline_ovr(gr)
g2$train(task)
g2$predict(task)
# Bagging outside OVR
g3 = po("replicate", reps = 3) %>>%
pipeline_ovr(po("subsample") %>>% learner) %>>%
po("classifavg", collect_multiplicity = TRUE)
g3$train(task)
g3$predict(task)
# }
Community examples
Looks like there are no examples yet.