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penaltyLearning (version 2020.5.13)

Penalty Learning

Description

Implementations of algorithms from Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression, by Hocking, Rigaill, Vert, Bach published in proceedings of ICML2013.

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Install

install.packages('penaltyLearning')

Monthly Downloads

938

Version

2020.5.13

License

GPL-3

Issues

1

Pull Requests

0

Stars

16

Forks

7

Maintainer

Toby Hocking

Last Published

May 14th, 2020

Functions in penaltyLearning (2020.5.13)

geom_tallrect

geom tallrect
plot.IntervalRegression

plot IntervalRegression
largestContinuousMinimumC

largestContinuousMinimumC
predict.IntervalRegression

predict IntervalRegression
IntervalRegressionInternal

IntervalRegressionInternal
largestContinuousMinimumR

largestContinuousMinimumR
targetIntervalROC

targetIntervalROC
targetIntervalResidual

targetIntervalResidual
coef.IntervalRegression

coef IntervalRegression
demo8

PeakSegFPOP demo data set
check_features_targets

check features targets
changeLabel

changeLabel
featureVector

featureVector
featureMatrix

featureMatrix
oneSkip

oneSkip
notConverging

Interval regression problem that was not converging
modelSelectionC

Exact model selection function
modelSelection

Compute exact model selection function
labelError

Compute incorrect labels
modelSelectionR

Exact model selection function
theme_no_space

theme no space
targetIntervals

Compute target intervals
neuroblastomaProcessed

Processed neuroblastoma data set with features and targets
print.IntervalRegression

print IntervalRegression
check_target_pred

check target pred
squared.hinge

squared hinge
IntervalRegressionCV

IntervalRegressionCV
GeomTallRect

GeomTallRect
ROChange

ROC curve for changepoints
IntervalRegressionUnregularized

IntervalRegressionUnregularized
IntervalRegressionRegularized

IntervalRegressionRegularized
change.colors

change colors
change.labels

change labels
IntervalRegressionCVmargin

IntervalRegressionCVmargin