A Comparison of Simultaneous Confidence Intervals to Identify Handwritten Digits

Nicolle Clements
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Nicolle Clements: Department of Decision System Sciences, Saint Joseph's University, Philadelphia, PA, USA

International Journal of Business Intelligence Research (IJBIR), 2014, vol. 5, issue 3, 29-40

Abstract: This paper evaluates the use of several known simultaneous confidence interval methods for the automated recognition of handwritten digits from data in a well-known handwriting database. Contained in this database are handwritten digits, 0 through 9, that were obtained from 42,000 participants' writing samples. The objective of the analyses is to utilize statistical testing procedures that can be easily automated by a computer to recognize which digit was written by a subject. The methodologies discussed in this paper are designed to be sensitive to Type I errors and will control an overall measure of these errors, called the Familywise Error Rate. The procedures were constructed based off of a training portion of the data set, then applied and validated on the remaining testing portion of the data.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jbir00:v:5:y:2014:i:3:p:29-40

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