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Additional to the preprocessing done there (see LibSVM site for details), this dataset was created as follows: \n-join test and train datasets (2 files, already pre-combined)\n-relabel classes 1,2=positive class and 3=negative class\n-normalize each file columnwise according to the following rules: \n-If a column only contains one value (constant feature), it will set to zero and thus removed by sparsity. \n-If a column contains two values (binary feature), the value occuring more often will be set to zero, the other to one. -If a column contains more than two values (multinary\/real feature), the column is divided by its std deviation.", "format": "Sparse_ARFF", "uploader": "aydin demircioglu", "uploader_id": 167, "visibility": "public", "creator": "M. Duarte, Y. H. 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