% The multi-feature digit dataset % ------------------------------- % % Oowned and donated by: % ---------------------- % % Robert P.W. Duin % Department of Applied Physics % Delft University of Technology % P.O. Box 5046, 2600 GA Delft % The Netherlands % % email: duin@ph.tn.tudelft.nl % http : //www.ph.tn.tudelft.nl/~duin % tel +31 15 2786143 % % Usage % ----- % A slightly different version of the database is used in % % M. van Breukelen, R.P.W. Duin, D.M.J. Tax, and J.E. den Hartog, Handwritten % digit recognition by combined classifiers, Kybernetika, vol. 34, no. 4, % 1998, 381-386. % % M. van Breukelen and R.P.W. Duin, Neural Network Initialization by Combined % Classifiers, in: A.K. Jain, S. Venkatesh, B.C. Lovell (eds.), ICPR'98, % Proc. 14th Int. Conference on Pattern Recognition (Brisbane, Aug. 16-20), % % The database as it is is used in: % % A.K. Jain, R.P.W. Duin, J. Mao, Statisitcal Pattern Recognition: A Review, % in preparation % % Description % ----------- % % This dataset consists of features of handwritten numerals (`0'--`9') % extracted from a collection of Dutch utility maps. 200 patterns per % class (for a total of 2,000 patterns) have been digitized in binary % images. These digits are represented in terms of the following six % feature sets (files): % % 1. mfeat-fou: 76 Fourier coefficients of the character shapes; % 2. mfeat-fac: 216 profile correlations; % 3. mfeat-kar: 64 Karhunen-Love coefficients; % 4. mfeat-pix: 240 pixel averages in 2 x 3 windows; % 5. mfeat-zer: 47 Zernike moments; % 6. mfeat-mor: 6 morphological features. % % In each file the 2000 patterns are stored in ASCI on 2000 lines. The % first 200 patterns are of class `0', followed by sets of 200 patterns % for each of the classes `1' - `9'. Corresponding patterns in different % feature sets (files) correspond to the same original character. % % The source image dataset is lost. Using the pixel-dataset (mfeat-pix) % sampled versions of the original images may be obtained (15 x 16 pixels). % % Total number of instances: % -------------------------- % 2000 (200 instances per class) % % Total number of attributes: % --------------------------- % 649 (distributed over 6 datasets,see above) % % no missing attributes % % Total number of classes: % ------------------------ % 10 % % Format: % ------ % 6 files, see above. % Each file contains 2000 lines, one for each instance. % Attributes are SPACE separated and can be loaded by Matlab as % > load filename % No missing attributes. Some are integer, others are real. % % % Information about the dataset % CLASSTYPE: nominal % CLASSINDEX: last % @relation mfeat @attribute att1 numeric @attribute att2 numeric @attribute att3 numeric @attribute att4 numeric @attribute att5 numeric @attribute att6 numeric @attribute class {1,2,3,4,5,6,7,8,9,10} @data 1.0,0.0,0.0,133.1508614,1.31169276,1620.22177892,1 1.0,0.0,0.0,126.7248614,1.30274497,1609.33482208,1 1.0,0.0,0.0,131.1738614,1.31903101,1568.97843469,1 1.0,0.0,0.0,129.4788614,1.27087816,1695.05528143,1 1.0,0.0,0.0,127.2628614,1.32963668,1647.72023493,1 1.0,0.0,0.0,131.0588614,1.31040314,2027.21136662,1 1.0,0.0,0.0,138.4428614,1.3799056,1918.75047185,1 1.0,0.0,0.0,129.3468614,1.30564601,1547.26372726,1 1.0,0.0,0.0,139.5428614,1.37466149,1871.05593439,1 1.0,0.0,0.0,132.6288614,1.37443436,1884.68045797,1 1.0,0.0,0.0,128.6848614,1.31939425,1624.01155591,1 1.0,0.0,0.0,129.3468614,1.21089933,1635.04409893,1 1.0,0.0,0.0,141.0728614,1.3362162,2180.62914883,1 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