pathClass is a collection of classification methods that use information about feature connectivity in a biological network as an additional source of information. This additional knowledge is incorporated into the classification a priori. Several authors have shown that this approach significantly increases the classification performance.
|Date of publication||2013-07-01 07:43:40|
|Maintainer||Marc Johannes <JohannesMarc@gmail.com>|
|License||GPL (>= 2)|
adjacency.matrix: An adjacency matrix of a random graph
as.adjacencyList: Uses a adjacency matrix to create a adjacency list
calc.diffusionKernel: Calculation of diffusion kernel matrix
crossval: Performs cross-validation with a specified algorithm
desummarize.ranks: Desummarize GeneRanks back to the corresponding probesets
extractFeatures: Extracts features which have been choosen by the...
fit.graph.svm: Implementation of a supervised classification framework...
fit.networkBasedSVM: Implementation of the network-based Support Vector Machine...
fit.rfe: Recursive Feature Elimination (RFE)
fit.rrfe: Reweighted Recursive Feature Elimination (RRFE)
getGeneRanks: Calculate GeneRanks as used by RRFE
mapping: A mapping of Refseq Protein IDs to probe set IDs for the gene...
matchMatrices: Matches the expression data to the adjacency matrix using the...
pathClass-package: Classification with SMVs and prior knowledge
plot.pathClassResult: Prints the result of one or more cross-validation run(s)
predict.graphSVM: Predict Method for Graph-SVM Fits
predict.networkBasedSVM: Predict Method for Network-based SVM Fits
predict.rfe: Predict Method for RFE Fits
predict.rrfe: Predict Method for RRFE Fits
read.hprd: Parse the HPRD flat file
summarizeProbes: Summarize probe sets
x: Example gene expression data
y: Example class labels for the gene expression data