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A regression-based method for the prediction of the indecisiveness degree through eye movement patterns

The development of eye-tracking-based methods to describe a person's indecisiveness is not commonly explored, even though research has shown that indecisiveness is involved in many unwanted cognitive states, such as a reduction in self-confidence during the decision-making process, doubts about past decisions, reconsidering, trepidation, distractibility, procrastination, neuroticism and even revenge. The purpose of our work is to propose a predictive model of a subject's degree of indecisiveness. To reach this goal, we first need to extract statistically relevant. Using eye-tracking methodology, we build a list of patterns that best distinguish decisive people from indecisive people; this segmentation is made according to the state of the art. The final list of eye-tracking patterns is also coherent with the state of art. A comparison between Multiple Linear Regression (MLR) and Support Vector Regression (SVR) is made so as to select the best predictive model.