buildAttributes: build attributes for an object depending on its class
In elqumsan/RNAseqMVA: Application of Multivariate Analysis methods to RNA-seq Data

Description Usage Arguments Value Author(s)

building all the attributes for the object based on its own class. in order to give it some certian features based on its own class e.g. we have DataTableWithClases, dataTableWithTrainTestSets, ect.

1	buildAttributes(self)

self

which is dataTable (a data.frame) with one row per feature (genes) and one column per individuals (sample)

an object that has all required attributes as in the following attributes.

nbSamples: that is the number of samples in relatedness object.
nbGenes: that is the number of genes in relatedness object.
sampleNames: that is the names of all samples involved in related object.
featureNames: that is names of all genes in the relatedness object.
classLabels: that is the class labels for all the samples in the relatedness object.
classNames: that is the names of all classes included in the relatedness object.
nbClasses: that is the overall number of the classes involved in the relatedness object.
classProperities: that is the data.frame composed of two columns one for the class name, number of samples in each class, train size per class
samplesPerClass: such paraperter are involved in classProperities.
classFrequencies: such parameter means the ratio of certain samples for somehow class so as to the whole samples into the dataTable.
randExpectedHitRate: it is corss product for the classFrequensies .
randExpectedMisclassificationRate: it is 1 - randExpectedHitRate.
sampleColors: such parameter for visualisation of the sample by putting some useful colors.