locClass: Collection of Local Classification Methods
Version 0.1-1

Collection of diverse local classification methods such as local versions of linear discriminant analysis, Fisher discriminant analysis and logistic regression.

AuthorJulia Schiffner and Stefanie Hillebrand
Date of publicationNone
MaintainerJulia Schiffner <schiffner@statistik.tu-dortmund.de>
LicenseGPL-2
Version0.1-1
URL http://www.statistik.tu-dortmund.de
Package repositoryView on R-Forge
InstallationInstall the latest version of this package by entering the following in R:
install.packages("locClass", repos="http://R-Forge.R-project.org")

Popular man pages

daqda: Discriminant Adaptive Quadratic Discriminant Analysis
FLXMCLconstant: Mixtures of Constant Classifiers
predict.wsvm: Predict New Examples by a Trained (Weighted) Support Vector...
svmModel: Combine Model-based Recursive Partitioning with Support...
wlda: Weighted Linear Discriminant Analysis
wqda: Weighted Quadratic Discriminant Analysis
wsvm: Weighted Support Vector Machines
See all...

All man pages Function index File listing

Man pages

constant: Constant Classifier
constantModel: Combine Model-based Recursive Partitioning with a Constant...
dalda: Discriminant Adaptive Linear Discriminant Analysis
dalr: Discriminant Adaptive Logistic Regression
damultinom: Discriminant Adaptive Multinomial Log-linear Models
dannet: Discriminant Adaptive Neural Network
daqda: Discriminant Adaptive Quadratic Discriminant Analysis
dasvm: Discriminant Adaptive Support Vector Machine
FLXMCL: Class "FLXMCL"
FLXMCLconstant: Mixtures of Constant Classifiers
FLXMCLlda: Mixtures of Linear Discriminant Analysis Models
FLXMCLmultinom: Mixtures of Multinomial Regression Models
FLXMCLnnet: Mixtures of Neural Networks
FLXMCLqda: Mixtures of Quadratic Discriminant Analysis Models
FLXMCLsvm: Mixtures of Support Vector Machines
FLXPwlda: Creator Function for the Concomitant Variable Model based on...
FLXPwlda-class: Class "FLXPwlda"
kda: Kernel Classification Rules
kmc: K-Means Classification
ldaModel: Combine Model-based Recursive Partitioning with Linear...
multinomModel: Combine Model-based Recursive Partitioning with Multinomial...
myfitted: Extract Fitted Values
mypredict: Predict Values
nnetGradient: Calculate value of objective function and gradient for a...
nnetModel: Combine Model-based Recursive Partitioning with Neural...
oslda: Observation Specific Linear Discriminant Analysis
osmultinom: Observation Specific Multinomial Log-linear Models
osnnet: Observation Specific Neural Networks
osqda: Observation Specific Quadratic Discriminant Analysis
ossvm: Observation Specific Support Vector Machines
predict.constant: Classify Multivariate Observations Based on the Constant...
predict.dalda: Classify Multivariate Observations Based on Discriminant...
predict.dalr: Classify Multivariate Observations Based on Discriminant...
predict.damultinom: Predict New Examples by a Trained Discriminant Adaptive...
predict.dannet: Predict New Examples by a Trained Discriminant Adaptive...
predict.daqda: Classify Multivariate Observations Based on Discriminant...
predict.dasvm: Predict Method for Discriminant Adaptive Support Vector...
predict.kda: Classify Multivariate Observations Based on Kernel Rules
predict.kmc: K-means Classification
predict.oslda: Classify Multivariate Observations Based on Observation...
predict.osmultinom: Predict New Examples Based on Observation Specific...
predict.osnnet: Predict New Examples Based on Observation Specific Neural...
predict.osqda: Classify Multivariate Observations Based on Observation...
predict.ossvm: Predict New Observations with Observation Specific Support...
predict.wlda: Classify Multivariate Observations Based on Weighted Linear...
predict.wqda: Classify Multivariate Observations Based on Weighted...
predict.wsvm: Predict New Examples by a Trained (Weighted) Support Vector...
qdaModel: Combine Model-based Recursive Partitioning with Quadratic...
svmModel: Combine Model-based Recursive Partitioning with Support...
wfs: Generation of Window Functions
wlda: Weighted Linear Discriminant Analysis
wqda: Weighted Quadratic Discriminant Analysis
wsvm: Weighted Support Vector Machines

Functions

Files

R
R/dasvm.R
R/Model_svm.R
R/daqda.R
R/dannet.R
R/checkwf.R
R/generatewf.R
R/FLXP.R
R/Model_multinom.R
R/wlda.R
R/Model_qda.R
R/oslda.R
R/kda.R
R/constant.R
R/damultinom.R
R/Model_nnet.R
R/dalda.R
R/ossvm.R
R/Model_lda.R
R/FLXMCL.R
R/FLXMCLlda.R
R/osqda.R
R/Model_constant.R
R/wsvm.R
R/kmc.R
R/FLXMCLconstant.R
R/FLXMCLmultinom.R
R/FLXMCLsvm.R
R/FLXMCLqda.R
R/dalr.R
R/osnnet.R
R/osmultinom.R
R/FLXMCLnnet.R
R/wqda.R
COPYRIGHT_LIBSVM
NAMESPACE
inst
inst/tests
inst/tests/test_FLXMCLconstant.R
inst/tests/test_osnnet.R
inst/tests/test_dasvm.R
inst/tests/test_wqda.R
inst/tests/test_damultinom.R
inst/tests/test_mobMultinomModel.R
inst/tests/test_constant.R
inst/tests/test_wlda.r
inst/tests/test_FLXMCLnnet.R
inst/tests/test_FLXMCLlda.R
inst/tests/test_mobLdaModel.R
inst/tests/test_dannet.R
inst/tests/test_daqda.R
inst/tests/test_osmultinom.R
inst/tests/test_mobSvmModel.R
inst/tests/test_wsvm.R
inst/tests/test_dalda.r
inst/tests/test_FLXMCLqda.R
inst/tests/test_ossvm.R
inst/tests/test_kda.R
inst/tests/test_FLXMCLmultinom.R
inst/tests/test_osqda.R
inst/tests/test_mobNnetModel.R
inst/tests/test_mobQdaModel.R
inst/tests/test_FLXMCLsvm.R
inst/tests/test_dalr.r
inst/tests/test_oslda.R
inst/tests/test_mobConstantModel.R
DESCRIPTION
man
man/predict.wsvm.Rd
man/oslda.Rd
man/FLXMCLconstant.Rd
man/osmultinom.Rd
man/mypredict.Rd
man/nnetGradient.Rd
man/dalda.Rd
man/myfitted.Rd
man/predict.kmc.Rd
man/predict.dannet.Rd
man/FLXMCLlda.Rd
man/constantModel.Rd
man/FLXMCL.Rd
man/ldaModel.Rd
man/wlda.Rd
man/predict.dalr.Rd
man/multinomModel.Rd
man/kmc.Rd
man/predict.oslda.Rd
man/predict.daqda.Rd
man/wsvm.Rd
man/svmModel.Rd
man/predict.dasvm.Rd
man/wqda.Rd
man/FLXPwlda-class.Rd
man/qdaModel.Rd
man/predict.dalda.Rd
man/dasvm.Rd
man/wfs.Rd
man/osnnet.Rd
man/predict.wqda.Rd
man/FLXMCLnnet.Rd
man/constant.Rd
man/predict.osnnet.Rd
man/FLXMCLsvm.Rd
man/kda.Rd
man/osqda.Rd
man/dannet.Rd
man/FLXMCLmultinom.Rd
man/dalr.Rd
man/predict.wlda.Rd
man/predict.damultinom.Rd
man/daqda.Rd
man/FLXPwlda.Rd
man/nnetModel.Rd
man/predict.constant.Rd
man/predict.kda.Rd
man/damultinom.Rd
man/FLXMCLqda.Rd
man/predict.osqda.Rd
man/predict.osmultinom.Rd
man/ossvm.Rd
man/predict.ossvm.Rd
src
src/sparse.h
src/predkda.c
src/svm.cpp
src/wf.c
src/sparse.c
src/Makevars
src/mynnet.h
src/wf.h
src/predossvm.c
src/predosqda.c
src/predosnnet.c
src/predoslda.c
src/svm.h
src/wsvm.c
locClass documentation built on May 21, 2017, 1:16 a.m.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs in the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.