We propose a hybrid FS method (mAP-KL), which combines multiple hypothesis testing and affinity propagation (AP)-clustering algorithm along with the Krzanowski & Lai cluster quality index, to select a small yet informative subset of genes.
|Date of publication||None|
|Maintainer||Argiris Sakellariou <email@example.com>|
|License||GPL (>= 2)|
annotate: Genome annotation of the "exemplars".
Annot-class: Class "Annot"
classification: Classify samples according to the SVM algorithm
Classify-class: Class "Classify"
DataLD-class: Class "DataLD"
loadFiles: Imports gene expression data
mAPKL: The mAP-KL algorithm
mAPKL-package: A hybrid feature selection method for gene expression data
mAPKLRes-class: Class "mAPKLRes"
metrics: Computes several clasification metrics
NetAttr-class: Class "NetAttr"
netwAttr: Calculates network characteristics
preprocess: Performs normalization and/or log2 transformation
probes2pathways: Extract pathways from "exemplars"
report: Produce an HTML report of the mAP-KL analysis
sampling: Splits a dataset to a train and a test sets of a user defined...