In this article, we propose a random walk-based model to predict legislators’ votes on a set of bills. In particular, we first convert roll call data, i.e. the recorded votes a...
Prediction of time series is an important problem in many areas of science and engineering. Extending the horizon of predictions further to the future is the challenging and diffic...
We define a new model of quantum learning that we call Predictive Quantum (PQ). This is a quantum analogue of PAC, where during the testing phase the student is only required to a...
—Predictive modeling aims at constructing models that predict a target property of an object based on its descriptions. In digital human modeling, it can be applied to predicting...
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...