DMwR: Functions and data for "Data Mining with R"
Version 0.4.1

This package includes functions and data accompanying the book "Data Mining with R, learning with case studies" by Luis Torgo, CRC Press 2010.

AuthorLuis Torgo
Date of publication2013-08-08 19:46:37
MaintainerLuis Torgo <ltorgo@dcc.fc.up.pt>
LicenseGPL (>= 2)
Version0.4.1
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("DMwR")

Getting started

Package overview

Popular man pages

DMwR-package: Functions and data for the book "Data Mining with R"
knnImputation: Fill in NA values with the values of the nearest neighbours
lofactor: An implementation of the LOF algorithm
PRcurve: Plot a Precision/Recall curve
SMOTE: SMOTE algorithm for unbalanced classification problems
SoftMax: Normalize a set of continuous values using SoftMax
unscale: Invert the effect of the scale function
See all...

All man pages Function index File listing

Man pages

algae: Training data for predicting algae blooms
algae.sols: The solutions for the test data set for predicting algae...
bestScores: Obtain the best scores from an experimental comparison
bootRun-class: Class "bootRun"
bootSettings-class: Class "bootSettings"
bootstrap: Runs a bootstrap experiment
centralImputation: Fill in NA values with central statistics
centralValue: Obtain statistic of centrality
class.eval: Calculate Some Standard Classification Evaluation Statistics
compAnalysis: Analyse and print the statistical significance of the...
compExp-class: Class "compExp"
CRchart: Plot a Cumulative Recall chart
crossValidation: Run a Cross Validation Experiment
cvRun-class: Class "cvRun"
cvSettings-class: Class "cvSettings"
dataset-class: Class "dataset"
dist.to.knn: An auxiliary function of 'lofactor()'
DMwR-defunct: Defunct Functions in Package 'DMwR'
DMwR-package: Functions and data for the book "Data Mining with R"
dsNames: Obtain the name of the data sets involved in an experimental...
experimentalComparison: Carry out Experimental Comparisons Among Learning Systems
expSettings-class: Class "expSettings"
getFoldsResults: Obtain the results on each iteration of a learner
getSummaryResults: Obtain a set of descriptive statistics of the results of a...
getVariant: Obtain the learner associated with an identifier within a...
growingWindowTest: Obtain the predictions of a model using a growing window...
GSPC: A set of daily quotes for SP500
hldRun-class: Class "hldRun"
hldSettings-class: Class "hldSettings"
holdOut: Runs a Hold Out experiment
join: Merging several 'compExp' class objects
kNN: k-Nearest Neighbour Classification
knneigh.vect: An auxiliary function of 'lofactor()'
knnImputation: Fill in NA values with the values of the nearest neighbours
learner-class: Class "learner"
learnerNames: Obtain the name of the learning systems involved in an...
LinearScaling: Normalize a set of continuous values using a linear scaling
lofactor: An implementation of the LOF algorithm
loocv: Run a Leave One Out Cross Validation Experiment
loocvRun-class: Class "loocvRun"
loocvSettings-class: Class "loocvSettings"
manyNAs: Find rows with too many NA values
mcRun-class: Class "mcRun"
mcSettings-class: Class "mcSettings"
monteCarlo: Run a Monte Carlo experiment
outliers.ranking: Obtain outlier rankings
PRcurve: Plot a Precision/Recall curve
prettyTree: Visual representation of a tree-based model
rankSystems: Provide a ranking of learners involved in an experimental...
reachability: An auxiliary function of 'lofactor()'
regr.eval: Calculate Some Standard Regression Evaluation Statistics
ReScaling: Re-scales a set of continuous values into a new range using a...
resp: Obtain the target variable values of a prediction problem
rpartXse: Obtain a tree-based model
rt.prune: Prune a tree-based model using the SE rule
runLearner: Run a Learning Algorithm
sales: A data set with sale transaction reports
SelfTrain: Self train a model on semi-supervised data
sigs.PR: Precision and recall of a set of predicted trading signals
slidingWindowTest: Obtain the predictions of a model using a sliding window...
SMOTE: SMOTE algorithm for unbalanced classification problems
SoftMax: Normalize a set of continuous values using SoftMax
statNames: Obtain the name of the statistics involved in an experimental...
statScores: Obtains a summary statistic of one of the evaluation metrics...
subset-methods: Methods for Function subset in Package 'DMwR'
task-class: Class "task"
test.algae: Testing data for predicting algae blooms
tradeRecord-class: Class "tradeRecord"
tradingEvaluation: Obtain a set of evaluation metrics for a set of trading...
trading.signals: Discretize a set of values into a set of trading signals
trading.simulator: Simulate daily trading using a set of trading signals
ts.eval: Calculate Some Standard Evaluation Statistics for Time Series...
unscale: Invert the effect of the scale function
variants: Generate variants of a learning system

Functions

CRchart Man page Source code
DMwR Man page
DMwR-defunct Man page
DMwR-package Man page
Eq Source code
GSPC Man page
LinearScaling Man page Source code
PRcurve Man page Source code
ReScaling Man page Source code
SMOTE Man page Source code
SelfTrain Man page Source code
SoftMax Man page Source code
St Source code
algae Man page
algae.sols Man page
bestScores Man page Source code
bootRun Man page Source code
bootRun-class Man page
bootSettings Man page Source code
bootSettings-class Man page
bootstrap Man page Source code
centralImputation Man page Source code
centralValue Man page Source code
changed.text.rpart Source code
class.eval Man page Source code
classWF Man page Source code
compAnalysis Man page Source code
compExp Man page Source code
compExp-class Man page
crossValidation Man page Source code
cvRun Man page Source code
cvRun-class Man page
cvSettings Man page Source code
cvSettings-class Man page
dataset Man page Source code
dataset-class Man page
dist.to.knn Man page Source code
dsNames Man page Source code
expSettings Man page
expSettings-class Man page
experimentalComparison Man page Source code
getFoldsResults Man page Source code
getSummaryResults Man page Source code
getVariant Man page Source code
growClassWF Man page Source code
growRegrWF Man page Source code
growingWindowTest Man page Source code
hldRun Man page Source code
hldRun-class Man page
hldSettings Man page Source code
hldSettings-class Man page
holdOut Man page Source code
join Man page Source code
kNN Man page Source code
knnImputation Man page Source code
knneigh.vect Man page Source code
learner Man page Source code
learner-class Man page
learnerNames Man page Source code
lofactor Man page Source code
loocv Man page Source code
loocvRun Man page Source code
loocvRun-class Man page
loocvSettings Man page Source code
loocvSettings-class Man page
manyNAs Man page Source code
mcRun Man page Source code
mcRun-class Man page
mcSettings Man page Source code
mcSettings-class Man page
monteCarlo Man page Source code
outliers.ranking Man page Source code
plot,compExp,missing-method Man page
plot,cvRun,missing-method Man page
plot,hldRun,missing-method Man page
plot,mcRun,missing-method Man page
plot,tradeRecord,ANY-method Man page
plot.compExp Source code
plot.cvRun Source code
plot.hldRun Source code
plot.mcRun Source code
plot.tradeRecord Source code
prettyTree Man page Source code
rankSystems Man page Source code
reachability Man page Source code
regr.eval Man page Source code
regrWF Man page Source code
resp Man page Source code
rpartXse Man page Source code
rt.prune Man page Source code
runLearner Man page Source code
sales Man page
show,bootSettings-method Man page
show,compExp-method Man page
show,cvSettings-method Man page
show,dataset-method Man page
show,hldSettings-method Man page
show,learner-method Man page
show,loocvSettings-method Man page
show,mcSettings-method Man page
show,task-method Man page
show,tradeRecord-method Man page
showTab Source code
sigs.PR Man page Source code
slideClassWF Man page Source code
slideRegrWF Man page Source code
slidingWindowTest Man page Source code
smote.exs Source code
standardWF Source code
statNames Man page Source code
statScores Man page Source code
subset,ANY-method Man page
subset,compExp-method Man page Man page
subset-methods Man page
summary,bootRun-method Man page
summary,compExp-method Man page
summary,cvRun-method Man page
summary,hldRun-method Man page
summary,loocvRun-method Man page
summary,mcRun-method Man page
summary,tradeRecord-method Man page
summary.bootRun Source code
summary.compExp Source code
summary.cvRun Source code
summary.hldRun Source code
summary.loocvRun Source code
summary.mcRun Source code
summary.tradeRecord Source code
task Man page Source code
task-class Man page
test.algae Man page
timeseriesWF Source code
tradeRecord Man page Source code
tradeRecord-class Man page
trading.signals Man page Source code
trading.simulator Man page Source code
tradingEvaluation Man page Source code
ts.eval Man page Source code
tsClassWF Man page Source code
tsRegrWF Man page Source code
unscale Man page Source code
variants Man page Source code

Files

inst
inst/CITATION
NAMESPACE
data
data/algae.RData
data/sales.RData
data/GSPC.RData
data/testAlgae.RData
data/datalist
data/algaeSols.RData
R
R/classes.R
R/utils.R
R/trading.R
R/OR.R
R/DMwR-defunct.R
R/LOF.R
R/experiments.R
R/smote.R
R/kNN.R
R/selfTraining.R
R/trees.R
MD5
DESCRIPTION
man
man/algae.sols.Rd
man/statNames.Rd
man/experimentalComparison.Rd
man/knnImputation.Rd
man/mcRun-class.Rd
man/bootstrap.Rd
man/centralImputation.Rd
man/sales.Rd
man/loocvRun-class.Rd
man/SoftMax.Rd
man/getVariant.Rd
man/learner-class.Rd
man/SMOTE.Rd
man/trading.signals.Rd
man/slidingWindowTest.Rd
man/dsNames.Rd
man/cvRun-class.Rd
man/bootSettings-class.Rd
man/bootRun-class.Rd
man/PRcurve.Rd
man/reachability.Rd
man/hldRun-class.Rd
man/ReScaling.Rd
man/bestScores.Rd
man/loocvSettings-class.Rd
man/kNN.Rd
man/DMwR-defunct.Rd
man/centralValue.Rd
man/lofactor.Rd
man/cvSettings-class.Rd
man/regr.eval.Rd
man/subset-methods.Rd
man/LinearScaling.Rd
man/prettyTree.Rd
man/statScores.Rd
man/CRchart.Rd
man/unscale.Rd
man/hldSettings-class.Rd
man/rpartXse.Rd
man/crossValidation.Rd
man/SelfTrain.Rd
man/class.eval.Rd
man/dist.to.knn.Rd
man/manyNAs.Rd
man/knneigh.vect.Rd
man/variants.Rd
man/task-class.Rd
man/getFoldsResults.Rd
man/rt.prune.Rd
man/resp.Rd
man/expSettings-class.Rd
man/loocv.Rd
man/GSPC.Rd
man/join.Rd
man/tradingEvaluation.Rd
man/sigs.PR.Rd
man/mcSettings-class.Rd
man/algae.Rd
man/runLearner.Rd
man/test.algae.Rd
man/tradeRecord-class.Rd
man/compAnalysis.Rd
man/trading.simulator.Rd
man/dataset-class.Rd
man/ts.eval.Rd
man/monteCarlo.Rd
man/growingWindowTest.Rd
man/DMwR-package.Rd
man/outliers.ranking.Rd
man/learnerNames.Rd
man/getSummaryResults.Rd
man/rankSystems.Rd
man/compExp-class.Rd
man/holdOut.Rd
CHANGES
DMwR documentation built on May 19, 2017, 9:55 a.m.

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