This event has ended. Visit the official site or create your own event on Sched.
Click here to return to main conference site. For a one page, printable overview of the schedule, see this.
View analytic
Tuesday, June 28 • 5:21pm - 5:39pm
Interactive Naive Bayes using Shiny: Text Retrieval, Classification, Quantification

Log in to save this to your schedule and see who's attending!

Interactive Machine Learning (IML) is a relatively new area of ML where focused interactions between algorithms and humans allow for faster and more accurate model updates with respect to classical ML algorithms. By involving users directly in the process of optimizing the parameters of the ML model, it is possible to quickly improve the effectiveness of the model and also to understand why some values of the parameters of the model work better than others through low-cost trial and error and experimentation with inputs and outputs. In this talk, we show three interactive applications developed with the Shiny package on the problems of text retrieval, text classification and text quantification. These applications implement a probabilistic model that use the Naïve Bayes (NB) assumption which has been widely recognised as a good trade-off between efficiency and efficacy, but it achieves satisfactory results only when optimized properly. All these three applications provide a two-dimensional representation of probabilities that has been inspired by the approach named Likelihood Spaces. This representation provides an adequate data visualization to understand how parameters and costs optimization affects the performance of the retrieval/classification/quantification application in a real machine learning setting on standard text collections. We will show that this particular geometrical interpretation of the probabilistic model together with the interaction significantly improves not only the performance but also the understanding of the models and opens new perspectives for new research studies.

avatar for Giorgio Maria  Di Nunzio

Giorgio Maria Di Nunzio

Assistant Professor, Department of Information Engineering, University of Padua
Automated Text Classification | Naive Bayes | Cost Sensitive Learning | Interactive Machine Learning | Gamification for Machine Learning

Tuesday June 28, 2016 5:21pm - 5:39pm
SIEPR 130 366 Galvez St, Stanford, CA 94305

Attendees (79)