boot.strap.bn           Executes a bootstrap during the learning of a
                        BN structure
check.algorithms        Verifies the BN learning algorithms
check.dichotomic.one.var
                        Verify if one specific variable of a data set
                        is dichotomic
check.levels.one.variable
                        Check the levels of a categorical variable
check.na                Verify variables with NA
check.ordered.one.var   Verify if one specific variable of a data set
                        is an ordered factor
check.ordered.to.pa     Verifies if there are ordered factor variables
                        to be declared in the pa model building process
check.outliers          Indentifies and gives an option to remove
                        outliers
check.type.one.var      Verify the type of one variable
check.types             Verify types of variable
check.variables.to.be.ordered
                        Check if the variables need to be ordered
convert.confusion.matrix
                        Converts the position of any element of
                        confusion matrix to VP, FP, FN, VN
create.cluster          Create a Parallel Socket Cluster
create.dummies          Creates dummy variables in the data set and
                        remove master variables
dataQualiN              A qualitative data set to test functions
dataQuantC              A quantiative data set to test functions
gera.bn.structure       Learn the Bayesian Network structure from data
                        and build a PA model
gera.pa                 Generates a PA model
gera.pa.model           Generates PA input model
mount.wl.bl.list        Mounts a white or black list
outcome.predictor.var   Builds a black list of predictor and/or outcome
                        variable
preprocess.outliers     Extract information of outliers
transf.into.ordinal     Transform categorical variables into ordinal
