Multiple Features Data Set of Robert P.W. Duin.
This dataset consists of features of handwritten numerals (‘0’–‘9’) (K=10) extracted from a collection of Dutch utility maps.
Two hundred patterns per class (for a total of 2,000 (=N) patterns)
have been digitized in binary images.
Raw observations are 32x45 bitmmaps, which are divided into
nooverlapping blocks of 2x3 and the number of pixels are counted in
This generate p=240 (16x15) variable, recodring the
normalized counts of pixels in each block and each element is an
integer in the range 0 to 6.
DutchUtility contains the true digits and
colnames of it contains the position of the block matrix, from which the normalized counts of pixels are taken.
A scalar containing integers between 1 and 2000.
Specify the size of the title text with a numeric value of length 1.
The original dataset is freely available from USIMachine Learning Repository (Frank and Asuncion (2010)) website http://archive .ics.uci.edu/ml/datasets.html.
Yumi Kondo <email@example.com>
Frank A, Asuncion A (2010). UCI Machine Learning Repository." http://archive.ics.uci.edu/ml.
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## Not run: data(DutchUtility) truedigit <- rownames(DutchUtility) (re <- RSKC(DutchUtility,ncl=10,alpha=0.1,L1=5.7,nstart=1000)) Sensitivity(re$labels,truedigit) table(re$labels,truedigit) ## Check the bitmap of the trimmed observations showDigit(re$oW) ## Check the features which receive zero weights names(which(re$weights==0)) ## End(Not run)
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