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.
2015
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
19th International Conference on Theory and Practice of Digital Libraries, TPDL 2015
9783319245911
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3169622
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