obozinski.holdout: Obozinski's heuristic methods - holdout

In HEMDAG: Hierarchical Ensemble Methods for Directed Acyclic Graphs

Description

Compute the Obozinski's heuristic methods Max, And, Or (Obozinski et al., Genome Biology, 2008) applying a classical holdout procedure.

Usage

obozinski.holdout(
  S,
  g,
  testIndex,
  heuristic = "and",
  norm = FALSE,
  norm.type = NULL
)

Arguments

S	a named flat scores matrix with examples on rows and classes on columns.
g	a graph of class graphNEL. It represents the hierarchy of the classes.
testIndex	a vector of integer numbers corresponding to the indexes of the elements (rows) of the scores matrix S to be used in the test set.
heuristic	a string character. It can be one of the following three values: "max": run the method heuristic.max; "and": run the method heuristic.and; "or": run the method heuristic.or;
norm	a boolean value. Should the flat score matrix be normalized? By default norm=FALSE. If norm=TRUE the matrix S is normalized according to the normalization type selected in norm.type.
norm.type	a string character. It can be one of the following values: NULL (def.): none normalization is applied (norm=FALSE) maxnorm: each score is divided for the maximum value of each class; qnorm: quantile normalization. preprocessCore package is used;

Value

A matrix with the scores of the classes corrected according to the chosen heuristic algorithm. Rows of the matrix are shrunk to testIndex.

Examples

data(graph);
data(scores);
data(test.index);
S.and <- obozinski.holdout(S, g, testIndex=test.index, heuristic="and", norm=FALSE, norm.type=NULL);

HEMDAG documentation built on Feb. 12, 2021, 5:13 p.m.