splice.arff

是UCI数据库中的一些有代表性的数据集

% 
%         -- G. G. Towell, 1991;
%            "Symbolic Knowledge and Neural Networks: Insertion, Refinement, and
%            Extraction", PhD Thesis, University of Wisconsin - Madison.
% 
%         -- G. G. Towell and J. W. Shavlik, 1992;
%            "Interpretation of Artificial Neural Networks: Mapping 
%            Knowledge-based Neural Networks into Rules", In Advances in Neural
%            Information Processing Systems, volume 4, Morgan Kaufmann.
% 
%    (b) attributes predicted: given a position in the middle of a window
%        60 DNA sequence elements (called "nucleotides" or "base-pairs"),
%        decide if this is a
% 	a) "intron -> exon" boundary (ie) [These are sometimes called "donors"]
% 	b) "exon -> intron" boundary (ei) [These are sometimes called "acceptors"]
% 	c) neither                      (n)
%    (c) Results of study indicated that machine learning techniques (neural
%        networks, nearest neighbor, contributors' KBANN system) performed as
%        well/better than classification based on canonical pattern matching
%        (method used in biological literature).
% 
% 4. Relevant Information Paragraph:
%    Problem Description: 
%       Splice junctions are points on a DNA sequence at which `superfluous' DNA is
%       removed during the process of protein creation in higher organisms.  The