featsweepSigFe: Processed output data after using the function named...

In pijush1285/sigFeature: sigFeature: Significant feature selection using SVM-RFE & t-statistic

Description

The variable "featsweepSigFe" contains the output of the function named "sigCVError()". The features which are produced on the basis of frequency are used here to enumerate mean external cross validation (k-fold) errors and the standard deviation of the errors. Training and test samples are same which are initially produced after splitting the main sample set in to k-folds. In each iteration, k-1 folds are considered as training samples and remaining one fold is considered as testing samples. In this external cross validation procedure, feature numbers are increased one by one by using the expression values from training dataset as well as test dataset. After that, traning samples are trained to test the tesing samples dynamically. The number of un classified samples are averaged and are called as external cross validation error rate.

Usage

data("featsweepSigFe")

Format

The format is:
    List of 400
    $ :List of 3
        ..$ svm.list:List of 10
        .. ..$ :'data.frame':  1 obs. of  4 variables:
        .. .. ..$ gamma     : num 0.000244
        .. .. ..$ cost      : num 0.001
        .. .. ..$ error     : num 0.333
        .. .. ..$ dispersion: num NA
        .. ..$ :'data.frame':  1 obs. of  4 variables:
        .. .. ..$ gamma     : num 0.000244
        .. .. ..$ cost      : num 0.001
        .. .. ..$ error     : num 0.333
        .. .. ..$ dispersion: num NA
        .. ..$ :'data.frame':  1 obs. of  4 variables:
        .. .. ..$ gamma     : num 0.000244
        .. .. ..$ cost      : num 0.001
        .. .. ..$ error     : num 0.667
        .. .. ..$ dispersion: num NA
        .. ..$ :'data.frame':  1 obs. of  4 variables:
        .. .. ..$ gamma     : num 0.000244
        .. .. ..$ cost      : num 0.001
        .. .. ..$ error     : num 0.333
        .. .. ..$ dispersion: num NA
        .. ..$ :'data.frame':  1 obs. of  4 variables:
        .. .. ..$ gamma     : num 0.000244
        .. .. ..$ cost      : num 0.001
        .. .. ..$ error     : num 0.333
        .. .. ..$ dispersion: num NA
        .. ..$ :'data.frame':  1 obs. of  4 variables:
        .. .. ..$ gamma     : num 1
        .. .. ..$ cost      : num 1.78
        .. .. ..$ error     : num 0.667
        .. .. ..$ dispersion: num NA
        .. ..$ :'data.frame':  1 obs. of  4 variables:
        .. .. ..$ gamma     : num 0.000244
        .. .. ..$ cost      : num 0.001
        .. .. ..$ error     : num 0
        .. .. ..$ dispersion: num NA
        .. ..$ :'data.frame':  1 obs. of  4 variables:
        .. .. ..$ gamma     : num 0.000244
        .. .. ..$ cost      : num 0.001
        .. .. ..$ error     : num 0
        .. .. ..$ dispersion: num NA
        .. ..$ :'data.frame':  1 obs. of  4 variables:
        .. .. ..$ gamma     : num 0.000244
        .. .. ..$ cost      : num 0.001
        .. .. ..$ error     : num 0.5
        .. .. ..$ dispersion: num NA
        .. ..$ :'data.frame':  1 obs. of  4 variables:
        .. .. ..$ gamma     : num 0.000244
        .. .. ..$ cost      : num 0.001
        .. .. ..$ error     : num 0.5
        .. .. ..$ dispersion: num NA
        ..$ error   : num 0.367
        ..$ errorSD : num 0.233
        ...
    

Value

featsweepSigFe

Return the values stored in the variable.

Source

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE2280

References

O'Donnell RK, Kupferman M, Wei SJ, Singhal S et al. Gene expression signature predicts lymphatic metastasis in squamous cell carcinoma of the oral cavity. Oncogene 2005 Feb 10; 24(7):1244-51. PMID: 15558013

Examples

data(featsweepSigFe)
## maybe str(featsweepSigFe) ; plot(featsweepSigFe) ...

pijush1285/sigFeature documentation built on Sept. 11, 2021, 1:02 p.m.