83 semeion 1 **Author**: Semeion Research Center of Sciences of Communication **Source**: UCI **Please cite**: Semeion Research Center of Sciences of Communication, via Sersale 117, 00128 Rome, Italy Tattile Via Gaetano Donizetti, 1-3-5,25030 Mairano (Brescia), Italy. * Title: Semeion Handwritten Digit Data Set * Abstract: 1593 handwritten digits from around 80 persons were scanned, stretched in a rectangular box 16x16 in a gray scale of 256 values. * Source: The dataset was created by Tactile Srl, Brescia, Italy (http://www.tattile.it) and donated in 1994 to Semeion Research Center of Sciences of Communication, Rome, Italy (http://www.semeion.it), for machine learning research. For any questions, e-mail Massimo Buscema (m.buscema '@' semeion.it) or Stefano Terzi (s.terzi '@' semeion.it) * Data Set Information: 1593 handwritten digits from around 80 persons were scanned, stretched in a rectangular box 16x16 in a gray scale of 256 values.Then each pixel of each image was scaled into a bolean (1/0) value using a fixed threshold. Each person wrote on a paper all the digits from 0 to 9, twice. The commitment was to write the digit the first time in the normal way (trying to write each digit accurately) and the second time in a fast way (with no accuracy). The best validation protocol for this dataset seems to be a 5x2CV, 50% Tune (Train +Test) and completly blind 50% Validation * Attribute Information: This dataset consists of 1593 records (rows) and 256 attributes (columns). Each record represents a handwritten digit, orginally scanned with a resolution of 256 grays scale (28). Each pixel of the each original scanned image was first stretched, and after scaled between 0 and 1 (setting to 0 every pixel whose value was under tha value 127 of the grey scale (127 included) and setting to 1 each pixel whose orinal value in the grey scale was over 127). Finally, each binary image was scaled again into a 16x16 square box (the final 256 binary attributes). * Relevant Papers: M Buscema, MetaNet: The Theory of Independent Judges, in Substance Use & Misuse 33(2)1998, pp 439-461. 1 ARFF 2015-05-25T22:22:34 Public https://test.openml.org/data/v1/download/83/semeion.arff 83 Class study_14 public active 2024-01-10 13:53:37 0fb35a1d7db2f76c8587f9125abcf048