svmTrain {fgga} | R Documentation

## Binary SVM classification models for individual GO-term predictions

### Description

svmTrain delivers a set of binary SVM classifiers for different GO-terms.

### Usage

    svmTrain(nodeGraph, tableGOs, dxCharacterized, graphGO,
            kernelSVM = "radial")

### Arguments

`nodeGraph` | A character indicating a GO node label
`tableGOs` | A binary matrix with ‘n’ proteins (rows) by ‘m’ GO node labels (columns).
`dxCharacterized` | A data frame with ‘n’ protein coding genes (rows) by ‘f’ features (columns).
`graphGO` | A graphNEL graph with ‘m’ GO node labels.
`kernelSVM` | The kernel used to calculate the variance (default: radial).

### Details

Starting from sets of positively annotated protein sequences to different GO-terms in a GO subgraph, corresponding sets of negatively annotated protein sequences are computed using the inclusive separation policy proposed by Eisner et al. Training datasets for each GO-term are used to train binary Support Vector Machine (SVM) classifiers with a variety of kernel options.

### Value

`svmTrain` | A list of objects of “svm" class containing the fitted model.

### Author(s)

Flavio E. Spetale, Pilar Bulacio and Javier Murillo <spetale@cifasis-conicet.gov.ar>

### References

Chang, Chih-Chung and Lin, Chih-Jen: LIBSVM: a library for Support Vector Machines http://www.csie.ntu.edu.tw/~cjlin/libsvm

Eisner R, Poulin B, Szafron D, Lu P, Greiner R. Improving protein function prediction using the hierarchical structure of the Gene Ontology. In: Proc. IEEE CIBCB; 2005. p. 1–1

Spetale FE, Tapia E, Krsticevic F, Roda F, Bulacio P (2016). A Factor Graph Approach to Automated GO Annotation. PLOS ONE 11(1): e0146986

### See Also

`svmGO`

### Examples

    data(CfData)

    mygraphGO <- as(CfData[["graphCfGO"]], "graphNEL")

    # SVM training in four GO-terms
    modelSVMs <- lapply(CfData[["nodesGO"]][1:4], FUN = svmTrain,
                        tableGOs = CfData[["tableCfGO"]],
                        dxCharacterized = CfData[["dxCf"]],
                        graphGO = mygraphGO, kernelSVM = "radial")

[Package fgga version 1.2.0 Index]