InformationGainHeuristic | R Documentation |
Performs the feature-clustering using entropy-based filters.
D2MCS::GenericHeuristic
-> InformationGainHeuristic
new()
Empty function used to initialize the object arguments in runtime.
InformationGainHeuristic$new()
heuristic()
The algorithm find weights of discrete attributes basing on
their correlation with continuous class attribute. Particularly
Information Gain uses H(Class) + H(Attribute) - H(Class, Attribute)
InformationGainHeuristic$heuristic(col1, col2, column.names = NULL)
col1
A numeric vector or matrix required to perform the clustering operation.
col2
A numeric vector or matrix to perform the clustering operation.
column.names
an optional character vector with the names of both columns.
A numeric vector of length 1 or NA if an error occurs.
clone()
The objects of this class are cloneable with this method.
InformationGainHeuristic$clone(deep = FALSE)
deep
Whether to make a deep clone.
Dataset
, information.gain
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