In this demo, we present two applications which allow users to ‘see’ a geometric interpretation of the Bayes’ rule and interact with a Naïve Bayes text classifier on a real dataset, namely the Reuters-21578 newswire collection. The main objective of this demo is to show how the pattern recognition capabilities of the human increase the effectiveness of the classifier even when technical details are not known in advance or the user is not an expert in the field. These two applications were developed with the R package Shiny; they have been deployed online and they are freely accessible from the links indicated in the paper.
Teaching machine learning: A geometric view of Naïve Bayes
DI NUNZIO, GIORGIO MARIA
2015
Abstract
In this demo, we present two applications which allow users to ‘see’ a geometric interpretation of the Bayes’ rule and interact with a Naïve Bayes text classifier on a real dataset, namely the Reuters-21578 newswire collection. The main objective of this demo is to show how the pattern recognition capabilities of the human increase the effectiveness of the classifier even when technical details are not known in advance or the user is not an expert in the field. These two applications were developed with the R package Shiny; they have been deployed online and they are freely accessible from the links indicated in the paper.| File | Dimensione | Formato | |
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tpdl2015_dinunzio.pdf
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