% 1. TITLE: % 	Letter Image Recognition Data % %    The objective is to identify each of a large number of black-and-white%    rectangular pixel displays as one of the 26 capital letters in the English%    alphabet.  The character images were based on 20 different fonts and each%    letter within these 20 fonts was randomly distorted to produce a file of%    20,000 unique stimuli.  Each stimulus was converted into 16 primitive%    numerical attributes (statistical moments and edge counts) which were then%    scaled to fit into a range of integer values from 0 through 15.  We%    typically train on the first 16000 items and then use the resulting model%    to predict the letter category for the remaining 4000.  See the article%    cited above for more details.% % 2.USE IN STATLOG% 	2.1 Testing Mode% 		Train and Test% % 	2.2 Special PreProcessing% 		No% 	% 	2.3 Test Results% 				Error Rate 	TIME% 		Algorithm	Train	Test	Train	Test% 		--------------------------------------------	% 		Alloc80		0.065	0.064	39575	?% 		KNN		0	0.068	15	2135% 		LVQ		0.057	0.079	1487	48% 		QuaDisc		0.101	0.113	3736	1223% 		Cn2		0.021	0.115	40458	52% 		BayTree		0.015	0.124	276	7% 		NewId		0	0.128	1056	2% 		IndCart		0.010	0.130	1098	1020% 		C4.5		0.042	0.132	309	292% 		Dipol92		0.167	0.176	1303	80% 		Radial		0.220	0.233	?	?% 		LogDisc		0.234	0.234	5062	39% 		Ac2		0	0.245	2529	92% 		Castle		0.237	0.245	9455	2933	% 		Kohonen		0.218	0.252	?	?% 		Cal5		0.158	0.253	1033	8% 		Smart		0.287	0.295	400919	184% 		Discrim		0.297	0.302	326	84% 		BackProp	0.323	0.327	277445	22% 		Bayes		0.516	0.529	75	18% 		Itrule		0.585	0.594	22325	69% 		Default		0.955	0.960	?	?% 		Cascade		1.0% 		Cart		1.000% % 3. SOURCE Information and Paste Usage% 	3.1 Source%    		-- Creator: David J. Slate%      		-- Odesta Corporation; 1890 Maple Ave; Suite 115; Evanston, IL 60201%    		-- Donor: David J. Slate (dave@math.nwu.edu) (708) 491-3867   %    		-- Date: January, 1991% % 	3.2 Past Usage:%    	-- P. W. Frey and D. J. Slate (Machine Learning Vol 6 #2 March 91):% 	"Letter Recognition Using Holland-style Adaptive Classifiers".% %    	The research for this article investigated the ability of several% 	variations of Holland-style adaptive classifier systems to learn to% 	correctly guess the letter categories associated with vectors of 16% 	integer attributes extracted from raster scan images of the letters.% 	The best accuracy obtained was a little over 80%.  It would be% 	interesting to see how well other methods do with the same data.% % % 4. DATASET DESCRIPTION% 	Number of Instances: % 		20000% 		Train	15000% 		Test	 5000% % 	Number of Attributes: % 		16 (numeric features)% % 	NUMBER of CLASSES : 26 % 		capital letter	(26 values from A to Z)% 		% 		Class Distribution:%  		789 A	   766 B     736 C     805 D	 768 E	   775 F     773 G%  		734 H	   755 I     747 J     739 K	 761 L	   792 M     783 N%  		753 O	   803 P     783 Q     758 R	 748 S	   796 T     813 U%  		764 V	   752 W     787 X     786 Y	 734 Z% % 	Attribute Information:% % 	 	1.	x-box	horizontal position of box	(integer)% 	 	2.	y-box	vertical position of box	(integer)% 	 	3.	width	width of box			(integer)% 	 	4.	high 	height of box			(integer)% 	 	5.	onpix	total # on pixels		(integer)% 	 	6.	x-bar	mean x of on pixels in box	(integer)% 	 	7.	y-bar	mean y of on pixels in box	(integer)% 	 	8.	x2bar	mean x variance			(integer)% 		9.	y2bar	mean y variance			(integer)% 		10.	xybar	mean x y correlation		(integer)% 		11.	x2ybr	mean of x * x * y		(integer)% 		12.	xy2br	mean of x * y * y		(integer)% 		13.	x-ege	mean edge count left to right	(integer)% 		14.	xegvy	correlation of x-ege with y	(integer)% 		15.	y-ege	mean edge count bottom to top	(integer)% 		16.	yegvx	correlation of y-ege with x	(integer)%  % 		Missing Attribute Values: None% % CONTACTS% 	statlog-adm@ncc.up.pt% 	bob@stams.strathclyde.ac.uk% 	% % ================================================================================% % Num Instances:     20000% Num Attributes:    17% Num Continuous:    16 (Int 16 / Real 0)% Num Nominal:       1% Missing values:    0 /  0.0%%%     name                      type enum ints real     missing    distinct  (1)%   1 'x-box'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %   2 'y-box'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %   3 'width'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %   4 'high'                    Int    0% 100%   0%     0 /  0%    16 /  0%   0% %   5 'onpix'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %   6 'x-bar'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %   7 'y-bar'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %   8 'x2bar'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %   9 'y2bar'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %  10 'xybar'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %  11 'x2ybr'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %  12 'xy2br'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %  13 'x-ege'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %  14 'xegvy'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %  15 'y-ege'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %  16 'yegvx'                   Int    0% 100%   0%     0 /  0%    16 /  0%   0% %  17 'class'                   Enum   0% 100%   0%     0 /  0%    26 /  0%   0% % %%%%% Relabeled values in attribute 'class'%    From: 1                       To: A                   %    From: 2                       To: B                   %    From: 3                       To: C                   %    From: 4                       To: D                   %    From: 5                       To: E                   %    From: 6                       To: F                   %    From: 7                       To: G                   %    From: 8                       To: H                   %    From: 9                       To: I                   %    From: 10                      To: J                   %    From: 11                      To: K                   %    From: 12                      To: L                   %    From: 13                      To: M                   %    From: 14                      To: N                   %    From: 15                      To: O                   %    From: 16                      To: P                   %    From: 17                      To: Q                   %    From: 18                      To: R                   %    From: 19                      To: S                   %    From: 20                      To: T                   %    From: 21                      To: U                   %    From: 22                      To: V                   %    From: 23                      To: W                   %    From: 24                      To: X                   %    From: 25                      To: Y                   %    From: 26                      To: Z                   %@relation letter@attribute 'x-box' integer@attribute 'y-box' integer@attribute 'width' integer@attribute 'high' integer@attribute 'onpix' integer@attribute 'x-bar' integer@attribute 'y-bar' integer@attribute 'x2bar' integer@attribute 'y2bar' integer@attribute 'xybar' integer@attribute 'x2ybr' integer@attribute 'xy2br' integer@attribute 'x-ege' integer@attribute 'xegvy' integer@attribute 'y-ege' integer@attribute 'yegvx' integer@attribute 'class' { A, B, C, D, E, F, G, H, I, J, K, L, M, N, O, P, Q, R, S, T, U, V, W, X, Y, Z}@data2,4,4,3,2,7,8,2,9,11,7,7,1,8,5,6,Z4,7,5,5,5,5,9,6,4,8,7,9,2,9,7,10,P7,10,8,7,4,8,8,5,10,11,2,8,2,5,5,10,S4,9,5,7,4,7,7,13,1,7,6,8,3,8,0,8,H6,7,8,5,4,7,6,3,7,10,7,9,3,8,3,7,H4,7,5,5,3,4,12,2,5,13,7,5,1,10,1,7,F6,10,8,8,4,7,8,2,5,10,7,8,5,8,1,8,N1,0,2,0,1,6,10,7,2,7,5,8,2,7,4,9,R5,9,7,6,7,7,7,2,4,9,8,9,7,6,2,8,M1,0,2,1,1,5,7,8,6,7,6,6,2,8,3,8,D2,7,4,5,1,9,8,4,2,5,13,8,3,10,0,8,V3,11,5,8,3,13,4,5,3,12,1,8,2,6,4,9,A3,7,5,5,5,8,7,4,4,7,6,7,4,6,8,13,K3,8,5,6,4,8,8,4,5,9,5,4,3,8,3,7,D8,11,9,8,6,7,8,3,6,10,5,7,4,6,6,8,S7,11,10,8,9,9,7,3,6,10,4,7,5,6,4,9,H5,5,5,7,3,3,7,6,12,7,6,15,0,8,7,6,E2,4,5,3,2,7,8,2,9,11,7,7,1,8,5,6,Z4,7,6,5,4,8,9,8,4,7,7,7,3,8,3,8,O4,6,4,7,5,8,8,6,2,7,7,11,3,9,5,8,Q5,10,7,9,3,8,5,9,8,6,4,8,3,8,4,8,Q3,7,3,5,1,1,1,5,5,0,1,6,0,8,0,8,L1,1,2,1,0,7,9,4,2,7,13,8,2,10,0,8,V2,1,3,2,1,8,7,3,8,6,6,8,2,8,5,8,X8,9,10,8,12,7,6,5,5,7,6,8,7,10,6,9,V5,10,8,7,11,9,6,2,2,8,4,8,10,5,3,6,M5,6,5,4,3,4,9,1,7,10,10,6,1,10,2,4,Y2,5,4,4,3,9,6,4,6,10,4,6,2,8,3,8,D3,8,5,6,5,7,7,4,8,7,7,8,3,8,5,10,E4,7,6,5,4,11,7,3,5,10,1,4,5,9,1,7,N4,10,6,7,2,9,4,3,2,8,1,8,3,7,3,8,A3,4,4,3,3,7,7,6,7,7,6,5,2,8,3,7,D4,8,5,6,4,9,9,6,4,7,5,8,3,8,10,7,Z3,5,5,3,2,5,9,3,4,10,8,8,5,8,0,7,N4,11,5,8,2,7,7,4,4,7,6,8,3,8,4,8,X4,9,6,7,7,6,8,1,4,10,8,7,6,11,4,5,F6,9,5,4,2,6,9,4,5,4,4,10,5,10,2,8,N3,4,4,7,1,0,1,6,6,0,0,6,0,8,0,8,L4,5,6,4,3,7,8,2,5,10,6,6,5,9,1,7,N1,3,3,2,1,7,8,2,9,11,6,8,1,8,5,7,Z6,9,6,4,3,7,6,4,4,9,9,5,3,10,4,4,Y0,0,0,1,0,7,7,4,4,7,6,8,0,8,0,8,I8,11,8,8,9,4,10,2,3,9,8,7,9,13,3,5,W2,1,3,2,2,7,9,5,6,7,9,9,3,9,1,8,U6,10,4,5,2,8,7,6,5,9,4,7,5,9,5,9,O3,4,4,3,2,5,12,3,6,11,9,4,1,11,1,5,T4,5,6,4,4,7,6,5,5,8,5,8,3,7,5,6,O4,7,6,10,9,8,9,4,0,8,7,6,5,11,5,7,P2,3,2,2,1,4,9,5,6,12,9,10,1,9,2,7,C3,7,4,5,2,6,6,6,6,10,8,11,2,10,4,9,G4,8,6,6,8,8,7,5,3,7,7,7,6,10,8,9,B3,4,4,3,3,5,7,4,7,7,6,11,3,8,5,9,K8,8,8,6,5,3,10,3,4,11,10,8,8,10,2,6,W2,6,4,4,2,9,11,3,4,4,11,8,2,10,1,8,V4,6,6,4,5,7,11,2,2,7,8,8,6,11,1,8,W5,11,7,8,7,6,6,6,5,6,5,8,6,6,7,10,H4,9,4,7,4,7,8,3,12,9,6,8,0,8,7,7,Z1,4,2,3,1,9,6,2,6,12,4,9,1,7,1,7,J2,4,4,3,1,5,11,3,4,13,7,4,1,9,1,7,F5,10,7,8,6,7,7,8,5,7,6,5,4,8,3,7,D3,5,5,4,2,8,7,3,8,11,5,7,1,9,5,8,S8,13,7,8,3,7,8,3,9,13,5,6,2,9,5,5,T4,9,5,7,5,8,9,8,4,7,8,7,4,7,4,9,O2,6,3,4,3,8,7,5,9,7,7,7,1,8,7,8,Z3,9,4,7,3,6,7,10,6,7,6,7,2,8,9,10,B3,2,4,3,2,6,10,4,5,10,9,5,2,9,3,6,F6,9,10,7,11,10,5,3,2,9,4,8,11,6,4,7,M2,6,4,4,1,8,15,1,5,6,11,8,0,8,0,8,T7,11,5,6,3,6,7,5,4,7,4,7,5,8,5,7,O2,4,3,3,2,5,7,4,6,6,6,11,3,8,4,10,K1,4,3,3,1,7,7,2,9,11,6,8,1,8,5,8,Z3,4,4,3,1,5,13,3,6,12,9,4,1,11,1,5,T4,10,7,8,6,7,10,2,3,6,9,8,8,11,1,8,W3,5,5,3,2,6,2,2,2,5,2,8,2,6,3,6,A2,2,3,3,2,8,8,6,1,5,6,9,2,9,5,10,Q9,10,7,14,6,8,7,4,2,12,6,8,3,9,13,6,Z4,5,6,7,5,9,10,3,2,8,7,7,3,10,8,6,H5,9,8,6,8,6,6,3,4,7,5,8,7,10,7,6,R1,7,0,4,0,7,7,4,4,7,6,8,0,8,0,8,I2,4,4,3,3,7,8,4,4,9,5,8,2,6,3,10,R5,10,7,7,5,7,9,4,6,5,8,10,6,10,1,7,U4,7,4,5,3,7,6,12,4,7,12,8,3,9,0,8,U7,10,5,5,2,6,8,6,8,11,7,11,2,8,5,9,C5,9,6,7,4,8,7,8,5,7,6,8,3,8,3,8,O7,13,5,7,3,6,8,6,8,10,6,10,1,8,8,8,E5,10,7,7,5,10,6,4,7,11,3,6,4,6,4,8,D5,7,6,5,3,4,8,5,7,9,8,9,3,9,2,5,U3,4,5,3,3,9,7,3,5,11,3,6,2,7,3,9,R2,4,3,3,2,7,7,5,7,7,6,9,2,8,5,10,E6,10,6,8,4,6,7,6,7,10,8,11,2,9,5,9,G5,9,7,6,6,10,6,2,6,11,3,8,3,8,4,12,B4,10,7,7,2,8,7,3,0,7,0,8,3,7,2,8,A1,1,3,2,1,6,10,1,6,8,11,8,1,11,2,8,Y2,4,4,6,4,8,11,3,3,5,8,9,2,11,5,6,Y5,10,6,8,5,8,6,9,4,7,5,8,3,8,3,8,O7,10,7,7,5,7,6,7,8,11,6,11,2,11,5,9,G5,9,7,7,5,8,3,1,2,6,2,7,3,5,4,7,A3,4,4,3,1,5,9,5,7,12,9,10,1,10,3,7,C4,5,6,7,6,7,8,4,1,8,6,6,4,10,8,5,H4,11,6,8,8,7,7,3,4,7,6,8,7,10,8,6,R4,7,6,5,4,8,6,5,5,8,7,7,3,7,4,6,J4,7,5,5,3,8,7,12,1,6,9,8,8,6,0,8,M3,9,5,7,3,7,11,2,3,6,11,9,2,10,1,8,V2,3,4,2,2,8,8,3,5,9,4,7,2,6,3,10,R3,8,5,6,3,7,12,4,6,7,11,8,2,12,1,8,T5,8,7,9,7,8,9,4,5,7,7,8,5,7,10,10,J3,5,5,3,2,8,7,3,8,11,5,7,1,9,4,8,S6,11,8,9,9,9,7,5,2,6,6,10,8,8,5,10,G2,3,3,2,2,9,6,4,6,10,4,6,2,8,2,9,D2,0,2,1,1,8,6,6,5,6,5,9,2,8,5,10,G5,8,7,10,7,10,5,4,4,8,3,6,3,5,8,8,Z6,11,6,8,4,5,7,10,10,7,6,6,3,8,4,8,D1,3,3,2,1,6,3,2,2,5,2,8,1,6,1,7,A1,0,1,0,0,7,13,1,4,7,10,8,0,8,0,8,T2,3,3,1,1,7,7,6,5,7,6,9,2,9,4,10,G1,3,2,1,0,6,4,1,7,8,2,10,0,7,2,9,L6,9,8,7,8,8,4,7,3,7,6,7,8,7,6,3,W0,1,1,2,1,7,7,1,6,7,6,8,0,8,2,8,I6,8,9,7,10,6,8,5,3,6,5,8,13,9,5,8,M4,9,4,4,2,11,4,4,5,12,3,8,2,7,6,12,Q2,3,3,4,2,8,7,5,8,4,6,8,0,8,8,8,S9,14,8,8,5,7,4,4,8,9,5,9,3,8,9,9,Q3,6,5,4,1,8,8,4,2,6,14,8,3,10,0,8,V5,10,5,8,6,6,8,9,5,6,5,7,2,8,5,11,R7,9,5,13,5,7,8,5,3,11,7,7,3,9,11,6,Z4,9,5,7,5,5,8,6,4,8,7,9,3,8,7,10,P8,9,8,6,6,2,12,2,2,10,10,8,7,11,1,7,W3,10,5,7,2,7,7,0,9,14,6,8,0,8,1,8,I3,7,3,5,2,1,12,4,5,12,11,7,0,8,1,6,F5,8,6,10,8,7,9,5,5,7,6,7,4,9,9,7,F4,9,5,7,2,10,6,2,8,14,3,8,0,7,0,8,J5,9,5,7,2,3,12,4,4,10,12,7,3,10,1,8,V6,9,8,6,9,7,8,6,5,7,5,8,8,9,8,6,M9,13,10,8,6,11,11,7,3,4,7,9,9,13,3,6,M4,8,4,6,4,7,7,7,4,10,6,8,3,8,3,6,O1,3,3,1,1,8,8,2,5,14,5,8,1,7,0,8,J3,8,4,6,2,3,6,6,11,7,7,14,0,8,7,7,E6,9,8,5,4,9,3,3,2,9,3,9,8,2,1,9,M9,13,10,7,6,4,9,4,6,10,10,11,5,8,4,6,K5,9,7,6,6,5,10,5,5,10,8,3,1,10,3,7,P5,10,7,8,4,10,3,2,3,8,1,7,2,7,3,8,A2,5,3,3,2,6,7,5,5,9,7,10,2,9,4,9,G5,9,5,4,3,10,7,4,5,7,9,5,4,11,2,7,V2,2,3,3,2,8,7,3,8,6,6,7,2,8,5,7,X1,1,2,1,0,7,4,2,0,7,2,8,2,7,1,8,A6,10,8,8,5,8,6,3,9,12,4,9,3,6,8,9,Z4,9,5,6,5,7,6,7,6,6,8,10,2,11,9,7,S8,9,11,7,8,10,6,2,5,9,3,6,10,8,3,9,M4,10,4,8,4,7,8,3,12,9,6,8,0,8,7,7,Z4,8,5,6,3,7,7,12,1,7,9,8,8,6,0,8,M12,13,11,7,5,8,11,3,3,5,10,7,8,12,1,6,W7,11,7,8,5,5,10,0,8,11,9,6,1,9,3,4,T2,7,3,5,2,3,7,6,10,7,6,14,0,8,7,8,E1,3,0,4,0,7,7,4,4,7,6,8,0,8,0,8,I5,9,5,4,3,5,9,3,6,9,8,9,5,7,3,7,H4,9,5,7,3,6,8,7,7,7,10,9,3,9,1,8,U4,7,4,4,1,7,7,5,4,7,6,8,3,8,4,8,X3,3,4,2,1,4,12,3,2,10,11,7,2,11,1,8,V5,9,6,4,4,7,9,2,3,7,8,6,8,11,2,7,W3,4,5,3,3,10,6,3,7,10,3,6,2,8,3,9,D4,2,5,4,4,7,8,4,6,7,5,7,3,7,4,8,R3,5,5,4,2,8,7,3,7,10,6,7,1,9,5,8,S7,10,6,5,3,7,8,2,7,11,6,6,2,9,5,6,F5,7,6,6,6,8,6,5,4,7,5,8,7,9,6,3,N3,5,5,8,3,11,5,3,5,10,2,7,2,7,5,11,Z3,5,4,7,2,7,7,4,14,10,6,8,0,8,8,8,Z1,10,0,7,0,7,7,4,4,7,6,8,0,8,0,8,I8,12,6,9,5,7,11,3,3,13,5,4,3,9,9,9,J2,3,3,4,3,8,8,5,2,8,8,9,2,9,5,8,Q5,10,7,8,4,5,13,5,4,13,8,3,2,10,2,5,F2,7,2,5,1,13,2,7,5,14,2,11,0,7,0,8,J