"RCLS.chunk"Object of class RCLS.chunk.
Objects can be created by calls of the form new("RCLS.chunk", ...). Accessor methods for the slots are a.s(x = NULL),
a.levels(x = NULL), a.ntrain(x = NULL), a.train(x = NULL), a.Zr(x = NULL), a.ntest(x = NULL), a.test(x = NULL) and a.Zt(x = NULL),
where x stands for an object of class RCLS.chunk.
s:finite set of size \(s\) of classes \(\bm{\Omega} = \{\bm{\Omega}_{g}; \ g = 1, \ldots, s\}\).
levels:a character vector of length \(s\) containing class names \(\bm{\Omega}_{g}\).
ntrain:a vector of length \(s\) containing numbers of observations in train datasets \(Y_{\mathrm{train}g}\).
train:a list of length \(n_{\mathrm{D}}\) of data frames containing train datasets \(Y_{\mathrm{train}g}\) of length \(n_{\mathrm{train}g}\).
Zr:a list of factors of true class membership \(\bm{\Omega}_{g}\) for the train datasets.
ntest:number of observations in test dataset \(Y_{\mathrm{test}}\).
test:a data frame containing test dataset \(Y_{\mathrm{test}}\) of length \(n_{\mathrm{test}}\).
Zt:a factor of true class membership \(\bm{\Omega}_{g}\) for the test dataset.
D. M. Dziuda. Data Mining for Genomics and Proteomics: Analysis of Gene and Protein Expression Data. John Wiley & Sons, New York, 2010.