Martin Možina and Janez Demšar and Michael W Kattan and Blaz Zupan (2004) Nomograms for Visualization of Naive Bayesian Classifier. In: European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), September 20-24, 2004, Pisa.
Besides good predictive performance, the naive Bayesian classifier can also offer a valuable insight into the structure of the training data and effects of the attributes on the class probabilities. This structure may be effectively revealed through visualization of the classifier. We propose a new way to visualize the naive Bayesian model in the form of a nomogram. The advantages of the proposed method are simplicity of presentation, clear display of the effects of individual attribute values, and visualization of confidence intervals. Nomograms are intuitive and when used for decision support can provide a visual explanation of predicted probabilities. And finally, a naive Bayesian nomogram can be printed out and used for probability prediction without the use of computer or calculator.
|Item Type: ||Conference or Workshop Item (Paper)|
|Keywords: ||naivni Bayesov klasifikator, vizualizacija, nomogrami, naive Bayesian classifier, visualization, nomograms|
|Language of Content: ||English|
|Related URLs: |
|Institution: ||University of Ljubljana|
|Department: ||Faculty of Computer and Information Science|
|Divisions: ||Faculty of Computer and Information Science > Artificial Intelligence Laboratory|
|Item ID: ||154|
|Date Deposited: ||08 Nov 2004|
|Last Modified: ||06 Dec 2013 12:00|
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