Evaluation of a pointwise local visual pattern exploration method. - Guo, Zhenyu; Ward, Matthew O.; Rundensteiner, Elke A.; Ruiz, Carolina
Sensitivity analysis is a powerful method for discovering the significant factors that contribute to understanding the interaction between variables in multivariate datasets. A number of sensitivity analysis methods fall into the class of local analysis, in which the sensitivity is defined as the partial derivatives of a target variable with respect to a group of independent variables. In a recent paper, we presented a novel pointwise local pattern exploration system for visual sensitivity analysis. Using this system, analysts are able to explore local patterns and the sensitivity at individual data points, which reveals the relationships between a focal point and its neighbors. In this paper we present several evaluations of the system, including case studies with real datasets, user studies on the effectiveness of the visualizations and interactions, and a detailed description of the experience of a user.
Keywords: Diamond-like carbon; Local pattern visualization; Analytical models