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.. _digits_dataset: |
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Optical recognition of handwritten digits dataset |
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**Data Set Characteristics:** |
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:Number of Instances: 1797 |
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:Number of Attributes: 64 |
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:Attribute Information: 8x8 image of integer pixels in the range 0..16. |
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:Missing Attribute Values: None |
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:Creator: E. Alpaydin (alpaydin '@' boun.edu.tr) |
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:Date: July; 1998 |
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This is a copy of the test set of the UCI ML hand-written digits datasets |
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https://archive.ics.uci.edu/ml/datasets/Optical+Recognition+of+Handwritten+Digits |
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The data set contains images of hand-written digits: 10 classes where |
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each class refers to a digit. |
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Preprocessing programs made available by NIST were used to extract |
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normalized bitmaps of handwritten digits from a preprinted form. From a |
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total of 43 people, 30 contributed to the training set and different 13 |
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to the test set. 32x32 bitmaps are divided into nonoverlapping blocks of |
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4x4 and the number of on pixels are counted in each block. This generates |
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an input matrix of 8x8 where each element is an integer in the range |
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0..16. This reduces dimensionality and gives invariance to small |
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distortions. |
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For info on NIST preprocessing routines, see M. D. Garris, J. L. Blue, G. |
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T. Candela, D. L. Dimmick, J. Geist, P. J. Grother, S. A. Janet, and C. |
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L. Wilson, NIST Form-Based Handprint Recognition System, NISTIR 5469, |
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1994. |
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.. dropdown:: References |
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- C. Kaynak (1995) Methods of Combining Multiple Classifiers and Their |
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Applications to Handwritten Digit Recognition, MSc Thesis, Institute of |
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Graduate Studies in Science and Engineering, Bogazici University. |
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- E. Alpaydin, C. Kaynak (1998) Cascading Classifiers, Kybernetika. |
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- Ken Tang and Ponnuthurai N. Suganthan and Xi Yao and A. Kai Qin. |
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Linear dimensionalityreduction using relevance weighted LDA. School of |
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Electrical and Electronic Engineering Nanyang Technological University. |
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2005. |
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- Claudio Gentile. A New Approximate Maximal Margin Classification |
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Algorithm. NIPS. 2000. |
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