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DMwR (version 0.4.1)

Functions and data for "Data Mining with R"

Description

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

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Version

Install

install.packages('DMwR')

Monthly Downloads

206

Version

0.4.1

License

GPL (>= 2)

Maintainer

Luis Torgo

Last Published

August 8th, 2013

Functions in DMwR (0.4.1)

knnImputation

Fill in NA values with the values of the nearest neighbours
SelfTrain

Self train a model on semi-supervised data
experimentalComparison

Carry out Experimental Comparisons Among Learning Systems
resp

Obtain the target variable values of a prediction problem
getFoldsResults

Obtain the results on each iteration of a learner
getVariant

Obtain the learner associated with an identifier within a comparison
loocvRun-class

Class "loocvRun"
crossValidation

Run a Cross Validation Experiment
LinearScaling

Normalize a set of continuous values using a linear scaling
growingWindowTest

Obtain the predictions of a model using a growing window learning approach.
algae

Training data for predicting algae blooms
cvSettings-class

Class "cvSettings"
runLearner

Run a Learning Algorithm
statNames

Obtain the name of the statistics involved in an experimental comparison
statScores

Obtains a summary statistic of one of the evaluation metrics used in an experimental comparison, for all learners and data sets involved in the comparison.
centralImputation

Fill in NA values with central statistics
reachability

An auxiliary function of lofactor()
SoftMax

Normalize a set of continuous values using SoftMax
knneigh.vect

An auxiliary function of lofactor()
task-class

Class "task"
hldSettings-class

Class "hldSettings"
trading.simulator

Simulate daily trading using a set of trading signals
getSummaryResults

Obtain a set of descriptive statistics of the results of a learner
DMwR-defunct

Defunct Functions in Package DMwR
mcRun-class

Class "mcRun"
bestScores

Obtain the best scores from an experimental comparison
PRcurve

Plot a Precision/Recall curve
cvRun-class

Class "cvRun"
dsNames

Obtain the name of the data sets involved in an experimental comparison
ts.eval

Calculate Some Standard Evaluation Statistics for Time Series Forecasting Tasks
rt.prune

Prune a tree-based model using the SE rule
GSPC

A set of daily quotes for SP500
bootstrap

Runs a bootstrap experiment
slidingWindowTest

Obtain the predictions of a model using a sliding window learning approach.
bootSettings-class

Class "bootSettings"
mcSettings-class

Class "mcSettings"
class.eval

Calculate Some Standard Classification Evaluation Statistics
rankSystems

Provide a ranking of learners involved in an experimental comparison.
prettyTree

Visual representation of a tree-based model
test.algae

Testing data for predicting algae blooms
centralValue

Obtain statistic of centrality
loocvSettings-class

Class "loocvSettings"
rpartXse

Obtain a tree-based model
DMwR-package

Functions and data for the book "Data Mining with R"
algae.sols

The solutions for the test data set for predicting algae blooms
learnerNames

Obtain the name of the learning systems involved in an experimental comparison
kNN

k-Nearest Neighbour Classification
dist.to.knn

An auxiliary function of lofactor()
ReScaling

Re-scales a set of continuous values into a new range using a linear scaling
sales

A data set with sale transaction reports
holdOut

Runs a Hold Out experiment
tradingEvaluation

Obtain a set of evaluation metrics for a set of trading actions
bootRun-class

Class "bootRun"
learner-class

Class "learner"
dataset-class

Class "dataset"
expSettings-class

Class "expSettings"
join

Merging several compExp class objects
hldRun-class

Class "hldRun"
manyNAs

Find rows with too many NA values
lofactor

An implementation of the LOF algorithm
outliers.ranking

Obtain outlier rankings
monteCarlo

Run a Monte Carlo experiment
tradeRecord-class

Class "tradeRecord"
trading.signals

Discretize a set of values into a set of trading signals
loocv

Run a Leave One Out Cross Validation Experiment
subset-methods

Methods for Function subset in Package `DMwR'
CRchart

Plot a Cumulative Recall chart
sigs.PR

Precision and recall of a set of predicted trading signals
unscale

Invert the effect of the scale function
SMOTE

SMOTE algorithm for unbalanced classification problems
compExp-class

Class "compExp"
compAnalysis

Analyse and print the statistical significance of the differences between a set of learners.
regr.eval

Calculate Some Standard Regression Evaluation Statistics
variants

Generate variants of a learning system