Opening the Black Box: the Relationship between Neural Networks and Linear Discriminant Functions

Over the last ten years feed‐forward neural networks have become a popular tool for statistical decision making. During this time, they have been applied in many fields, including cytological classification. Neural networks are often treated as a black box, whose inner workings are concealed from th...

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Main Authors: Roger A. Kemp, Calum MacAulay, Branko Palcic
Format: Article
Language:English
Published: Wiley 1997-01-01
Series:Analytical Cellular Pathology
Online Access:http://dx.doi.org/10.1155/1997/646081
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author Roger A. Kemp
Calum MacAulay
Branko Palcic
author_facet Roger A. Kemp
Calum MacAulay
Branko Palcic
author_sort Roger A. Kemp
collection DOAJ
description Over the last ten years feed‐forward neural networks have become a popular tool for statistical decision making. During this time, they have been applied in many fields, including cytological classification. Neural networks are often treated as a black box, whose inner workings are concealed from the researcher. This is unfortunate, since the inner workings of a neural network can be understood in a manner similar to that of a linear discriminant function, which is the standard tool that researchers use for decision making.
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1878-3651
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spelling doaj-art-6e1c9c90e1cc4d51a746dee78cfb5d1b2025-08-20T03:33:56ZengWileyAnalytical Cellular Pathology0921-89121878-36511997-01-01141193010.1155/1997/646081Opening the Black Box: the Relationship between Neural Networks and Linear Discriminant FunctionsRoger A. Kemp0Calum MacAulay1Branko Palcic2BC Cancer Research Centre, Vancouver BC, V5Z 1L3, CanadaBC Cancer Research Centre, Vancouver BC, V5Z 1L3, CanadaBC Cancer Research Centre, Vancouver BC, V5Z 1L3, CanadaOver the last ten years feed‐forward neural networks have become a popular tool for statistical decision making. During this time, they have been applied in many fields, including cytological classification. Neural networks are often treated as a black box, whose inner workings are concealed from the researcher. This is unfortunate, since the inner workings of a neural network can be understood in a manner similar to that of a linear discriminant function, which is the standard tool that researchers use for decision making.http://dx.doi.org/10.1155/1997/646081
spellingShingle Roger A. Kemp
Calum MacAulay
Branko Palcic
Opening the Black Box: the Relationship between Neural Networks and Linear Discriminant Functions
Analytical Cellular Pathology
title Opening the Black Box: the Relationship between Neural Networks and Linear Discriminant Functions
title_full Opening the Black Box: the Relationship between Neural Networks and Linear Discriminant Functions
title_fullStr Opening the Black Box: the Relationship between Neural Networks and Linear Discriminant Functions
title_full_unstemmed Opening the Black Box: the Relationship between Neural Networks and Linear Discriminant Functions
title_short Opening the Black Box: the Relationship between Neural Networks and Linear Discriminant Functions
title_sort opening the black box the relationship between neural networks and linear discriminant functions
url http://dx.doi.org/10.1155/1997/646081
work_keys_str_mv AT rogerakemp openingtheblackboxtherelationshipbetweenneuralnetworksandlineardiscriminantfunctions
AT calummacaulay openingtheblackboxtherelationshipbetweenneuralnetworksandlineardiscriminantfunctions
AT brankopalcic openingtheblackboxtherelationshipbetweenneuralnetworksandlineardiscriminantfunctions