obozinski.holdout {HEMDAG}

Obozinski's heuristic methods – holdout

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:

1. "max": run the method heuristic.max;

2. "and": run the method heuristic.and;

3. "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:

1. NULL (def.): none normalization is applied (norm=FALSE)

2. maxnorm: each score is divided for the maximum value of each class;

3. 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);