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Two challenges of correct validation in pattern recognition

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journal contribution
posted on 2023-06-08, 18:35 authored by Thomas NowotnyThomas Nowotny
Supervised pattern recognition is the process of mapping patterns to class labels that define their meaning. The core methods for pattern recognition have been developed by machine learning experts but due to their broad success, an increasing number of non-experts are now employing and refining them. In this perspective, I will discuss the challenge of correct validation of supervised pattern recognition systems, in particular when employed by nonexperts. To illustrate the problem, I will give three examples of common errors that I have encountered in the last year. Much of this challenge can be addressed by strict procedure in validation but there are remaining problems of correctly interpreting comparative work on exemplary data sets, which I will elucidate on the example of the well-used MNIST data set of handwritten digits.

Funding

Green brain; G0924; EPSRC-ENGINEERING & PHYSICAL SCIENCES RESEARCH COUNCIL; EP/J019690/1

History

Publication status

  • Published

File Version

  • Published version

Journal

Frontiers in Robotics and AI

ISSN

2296-9144

Publisher

Frontiers

Issue

5

Volume

1

Page range

1-6

Department affiliated with

  • Informatics Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2014-10-01

First Open Access (FOA) Date

2014-10-01

First Compliant Deposit (FCD) Date

2014-10-01

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