TY - GEN
T1 - Visual techniques to compare predictive models
AU - Buono, Paolo
AU - Bertini, Enrico
AU - Legretto, Alessandra
AU - Costabile, Maria F.
N1 - Funding Information:
This work is funded by Italian MIUR through PON Ricerca e In-novazione 2014-2020 - Asse I "Investimenti in capitale umano" - Azione I.1 "Dottorati Innovativi con caratterizzazione industriale" (CUP: H96D17000040006) and Electronic Shopping & Home delivery of Edible goods with Low environmental Footprint (E-SHELF), POR Puglia FESR-FSE 2014-2020 (ID: OSW3NO1).
Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/9/23
Y1 - 2019/9/23
N2 - Predictive analysis is an important part of data analysis. Predictive models, based on Statistics or Machine Learning, are increasingly used to estimate, with a certain probability, future values of the variables that describe a phenomenon. Different models produce different results on a same dataset; thus, several models should be compared in order to identify the most suitable one. The paper is part of a larger research that aims at providing interactive visualizations that help the analysts to compare predictive models and to select the model that best fits the data. Specifically, two visualizations are presented, which support the analysts in performing some tasks of the Keim's Visual Analytics Mantra.
AB - Predictive analysis is an important part of data analysis. Predictive models, based on Statistics or Machine Learning, are increasingly used to estimate, with a certain probability, future values of the variables that describe a phenomenon. Different models produce different results on a same dataset; thus, several models should be compared in order to identify the most suitable one. The paper is part of a larger research that aims at providing interactive visualizations that help the analysts to compare predictive models and to select the model that best fits the data. Specifically, two visualizations are presented, which support the analysts in performing some tasks of the Keim's Visual Analytics Mantra.
KW - Comparison Matrix
KW - Pie-chart Matrix
KW - Visual Analytics
UR - http://www.scopus.com/inward/record.url?scp=85076697084&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85076697084&partnerID=8YFLogxK
U2 - 10.1145/3351995.3352035
DO - 10.1145/3351995.3352035
M3 - Conference contribution
AN - SCOPUS:85076697084
T3 - ACM International Conference Proceeding Series
BT - CHItaly 2019 - Proceedings of the 13th Biannual Conference of the Italian SIGCHI Chapter Designing the Next Interaction
PB - Association for Computing Machinery
T2 - 13th Biannual Conference of the Italian SIGCHI Chapter Designing the Next Interaction, CHItaly 2019
Y2 - 23 September 2019 through 25 September 2019
ER -