calculateMembershipFunctions: Calculates Membership Functions

In DFP: Gene Selection

Description

Calculates the Membership Functions. These functions are used in the next step (discretizeExpressionValues) to discretize gene expression data.

Usage

calculateMembershipFunctions(rmadataset, skipFactor = 3)

Arguments

rmadataset	ExpressionSet with numeric values containing gene expression values (rows) of samples belonging to different categories (columns). The ExpressionSet also contains an AnnotatedDataFrame with metadata regarding the classes to which each sample belongs.
skipFactor	Numeric value to omit odd values (a way of normalization). Higher values imply that less samples of a gene are considered as odd. If skipFactor=0 do NOT skip. Default value = 3. Range[0,).

Value

Membership functions to determine the discret value (linguistic label) corresponding to a given gene expression level.

Author(s)

Rodrigo Alvarez-Gonzalez
Daniel Glez-Pena
Fernando Diaz
Florentino Fdez-Riverola
Maintainer: Rodrigo Alvarez-Gonzalez <[e-mail]>

References

F. Diaz; F. Fdez-Riverola; D. Glez-Pena; J.M. Corchado. Using Fuzzy Patterns for Gene Selection and Data Reduction on Microarray Data. 7th International Conference on Intelligent Data Engineering and Automated Learning: IDEAL 2006, (2006) pp. 1095-1102

DFP documentation built on Nov. 8, 2020, 7:46 p.m.