DMwR2-package           Functions and data for the second edition of
                        the book "Data Mining with R"
GSPC                    A set of daily quotes for SP500
SelfTrain               Self train a model on semi-supervised data
SoftMax                 Normalize a set of continuous values using
                        SoftMax
algae                   Training data for predicting algae blooms
algae.sols              The solutions for the test data set for
                        predicting algae blooms
centralImputation       Fill in NA values with central statistics
centralValue            Obtain statistic of centrality
createEmbedDS           Creates an embeded data set from an univariate
                        time series
dist.to.knn             An auxiliary function of 'lofactor()'
kNN                     k-Nearest Neighbour Classification
knnImputation           Fill in NA values with the values of the
                        nearest neighbours
knneigh.vect            An auxiliary function of 'lofactor()'
lofactor                An implementation of the LOF algorithm
manyNAs                 Find rows with too many NA values
nrLinesFile             Counts the number of lines of a file
outliers.ranking        Obtain outlier rankings
reachability            An auxiliary function of 'lofactor()'
rpartXse                Obtain a tree-based model
rt.prune                Prune a tree-based model using the SE rule
sales                   A data set with sale transaction reports
sampleCSV               Drawing a random sample of lines from a CSV
                        file
sampleDBMS              Drawing a random sample of records of a table
                        stored in a DBMS
sigs.PR                 Precision and recall of a set of predicted
                        trading signals
sp500                   A set of daily quotes for SP500 in CSV Format
test.algae              Testing data for predicting algae blooms
tradeRecord-class       Class "tradeRecord"
trading.signals         Discretize a set of values into a set of
                        trading signals
trading.simulator       Simulate daily trading using a set of trading
                        signals
tradingEvaluation       Obtain a set of evaluation metrics for a set of
                        trading actions
