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KEEL-dataset - data set description
dataset/images/penbased.jpg



This section describes main characteristics of the penbased data set and its attributes:

General information

Pen-Based Recognition of Handwritten Digits data set
TypeClassificationOriginReal world
Features 16(Real / Integer / Nominal)(0 / 16 / 0)
Instances10992 Classes10
Missing values?No

Attribute description

AttributeDomainAttributeDomain
At1[0, 100]At9[0, 100]
At2[0, 100]At10[0, 100]
At3[0, 100]At11[0, 100]
At4[0, 100]At12[0, 100]
At5[0, 100]At13[0, 100]
At6[0, 100]At14[0, 100]
At7[0, 100]At15[0, 100]
At8[0, 100]At16[0, 100]
Class{0,1,2,3,4,5,6,7,8,9}

Additional information

A digit data base made by collecting 250 samples from 44 writers, using only (x, y) coordinate information represented as constant length feature vectors, which were resampled to 8 points per digit (therefore the data set contains 8 points x 2 coordinates = 16 attributes).

The class label represents the code of the digit written.




In this section you can download some files related to the penbased data set:

  • The complete data set already formatted in KEEL format can be downloaded from herezip.gif.
  • A copy of the data set already partitioned by means of a 10-folds cross validation procedure can be downloaded from herezip.gif.
  • A copy of the data set already partitioned by means of a 5-folds cross validation procedure can be downloaded from herezip.gif.
  • The header file associated to this data set can be downloaded from heretxt.png.
  • This is not a native data set from the KEEL project. It has been obtained from the UCI Machine Learning Repository . The original page where the data set can be found is: http://archive.ics.uci.edu/ml/datasets/Pen-Based+Recognition+of+Handwritten+Digits.


 
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