DTIC ADA220046: Improving Upon Standard Pattern Classification Algorithms By Implementing Them As Multi-Layer Perceptrons - Info and Reading Options
By Defense Technical Information Center
"DTIC ADA220046: Improving Upon Standard Pattern Classification Algorithms By Implementing Them As Multi-Layer Perceptrons" and the language of the book is English.
“DTIC ADA220046: Improving Upon Standard Pattern Classification Algorithms By Implementing Them As Multi-Layer Perceptrons” Metadata:
- Title: ➤ DTIC ADA220046: Improving Upon Standard Pattern Classification Algorithms By Implementing Them As Multi-Layer Perceptrons
- Author: ➤ Defense Technical Information Center
- Language: English
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- Internet Archive ID: DTIC_ADA220046
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"DTIC ADA220046: Improving Upon Standard Pattern Classification Algorithms By Implementing Them As Multi-Layer Perceptrons" Description:
The Internet Archive:
The multi-layer perceptron (MLP) is a type of adaptive layered network often used as a pattern classifier. In more recent literature, MLPs are compared with simpler classification techniques using common datasets. We select two of these simple static pattern classification algorithms and briefly review the relevant techniques. After introducing a modest set of evaluation databases, the performance of the standard classifiers and MLPs are assessed. A technique for implementing the two standard classifiers as MLPs is presented and this novel approach is used to automatically design a 'good' set of initial weights for the MLP networks. Encouraging experimental results for these hybrid techniques are shown for illustration. Keywords: Pattern recognition; Speech; Images; Artificial intelligence.
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- Internet Archive Link: Archive.org page
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- Added Date: 2018-02-25 17:51:21
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