Index of values

addData [Oc45.S]
Adds the given value to the training set.
addDataList [Oc45.S]
Adds a list of data vectors to the given training set.
avg [Oc45.Comparable]
A function that returns "the average" of its two arguments, or the closest thing to it.

c45 [Oc45.S]
Generates a decision tree from a training set.
classify [Oc45.S]
Classifies a data vector, given a decision tree.
compare [Oc45.Comparable]
A function such that compare a b is zero if a equals b and is strictly negative (resp.

emptyTrainSet [Oc45.S]
emptyTrainSet nbFeatures nbCategories featContinuity creates an empty train set with nbFeatures features and nbCategories categories.

getFeatContinuity [Oc45.S]
Returns the feature continuity array, see Oc45.S.emptyTrainSet.
getFeatureMax [Oc45.S]
Returns the feature bound array, see Oc45.S.setFeatureMax.
getNbCategories [Oc45.S]
Returns the number of categories.
getNbFeatures [Oc45.S]
Returns the number of features.
getSet [Oc45.S]
Extracts the data vector list from a training set.
getSetSize [Oc45.S]
Returns the number of training cases in a given training set.

setFeatureMax [Oc45.S]
setFeatureMax feat maxVal trainSet sets the maximum value the discrete feature feat may take.

toDot [Oc45.S]
Pretty-prints the given decision tree as a Dot file in the given formatter, using the second argument as a pretty-printer for the Oc45.S.contData type (ie., the type of a continuous data).
toDotStdout [Oc45.S]
Same as Oc45.S.toDot, but prints directly to stdout.