optidigits: Optical Recognition of Handwritten Digits
In PPCI: Projection Pursuit for Cluster Identification
Description
Usage
Format
Source
References
Description
This data set contains vectorised images of handwritten digits (0–9), compressed to 8x8 pixels.
Usage
1
Format
A list with entries $x (a 5620x64 matrix with each row corresponding to an image) and $c (a vector of labels indicating the written digit).
Source
UCI Machine Learning Repository.
References
Lichman, M. (2013) UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science. https://archive.ics.uci.edu/ml
PPCI documentation built on March 13, 2020, 3:27 a.m.
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Description Usage Format Source References
Description
This data set contains vectorised images of handwritten digits (0–9), compressed to 8x8 pixels.
Usage
1 |
Format
A list with entries $x (a 5620x64 matrix with each row corresponding to an image) and $c (a vector of labels indicating the written digit).
Source
UCI Machine Learning Repository.
References
Lichman, M. (2013) UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science. https://archive.ics.uci.edu/ml
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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