Commit Inicial

data/tanveer/optical/optdigits.names

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+1. Title of Database: Optical Recognition of Handwritten Digits
+
+2. Source:
+	E. Alpaydin, C. Kaynak
+	Department of Computer Engineering
+	Bogazici University, 80815 Istanbul Turkey
+	alpaydin@boun.edu.tr
+	July 1998
+
+3. Past Usage:
+	C. Kaynak (1995) Methods of Combining Multiple Classifiers and Their
+	Applications to Handwritten Digit Recognition, 
+	MSc Thesis, Institute of Graduate Studies in Science and 
+	Engineering, Bogazici University.
+
+	E. Alpaydin, C. Kaynak (1998) Cascading Classifiers, Kybernetika,
+	to appear. ftp://ftp.icsi.berkeley.edu/pub/ai/ethem/kyb.ps.Z
+
+4. Relevant Information:
+	We used preprocessing programs made available by NIST to extract
+	normalized bitmaps of handwritten digits from a preprinted form. From
+	a total of 43 people, 30 contributed to the training set and different
+	13 to the test set. 32x32 bitmaps are divided into nonoverlapping 
+	blocks of 4x4 and the number of on pixels are counted in each block.
+	This generates an input matrix of 8x8 where each element is an 
+	integer in the range 0..16. This reduces dimensionality and gives 
+	invariance to small distortions.
+
+	For info on NIST preprocessing routines, see 
+	M. D. Garris, J. L. Blue, G. T. Candela, D. L. Dimmick, J. Geist, 
+	P. J. Grother, S. A. Janet, and C. L. Wilson, NIST Form-Based 
+	Handprint Recognition System, NISTIR 5469, 1994.
+
+5. Number of Instances
+	optdigits.tra	Training	3823
+	optdigits.tes	Testing		1797
+	
+	The way we used the dataset was to use half of training for 
+	actual training, one-fourth for validation and one-fourth
+	for writer-dependent testing. The test set was used for 
+	writer-independent testing and is the actual quality measure.
+
+6. Number of Attributes
+	64 input+1 class attribute
+
+7. For Each Attribute:
+	All input attributes are integers in the range 0..16.
+	The last attribute is the class code 0..9
+
+8. Missing Attribute Values
+	None
+
+9. Class Distribution
+	Class:	No of examples in training set
+	0:  376
+	1:  389
+	2:  380
+	3:  389
+	4:  387
+	5:  376
+	6:  377
+	7:  387
+	8:  380
+	9:  382
+
+	Class: No of examples in testing set
+	0:  178
+	1:  182
+	2:  177
+	3:  183
+	4:  181
+	5:  182
+	6:  181
+	7:  179
+	8:  174
+	9:  180
+
+Accuracy on the testing set with k-nn 
+using Euclidean distance as the metric
+
+ k =  1   : 98.00
+ k =  2   : 97.38
+ k =  3   : 97.83
+ k =  4   : 97.61
+ k =  5   : 97.89
+ k =  6   : 97.77
+ k =  7   : 97.66
+ k =  8   : 97.66
+ k =  9   : 97.72
+ k = 10   : 97.55
+ k = 11   : 97.89
+