Importance of spatial predictor variable selection in machine learning applications – Moving from data reproduction to spatial prediction

Bayesian Prediction in Spatial Data Analysis

Local Spatial-Predictor Selection

Spatial Variable Importance Assessment for Yield Prediction in Precision Agriculture

Precision Agriculture applies state-of-the-art GPS technology in connection with site-specific, sensor-based crop management. It can also be described as a data-driven approach to agriculture, which is strongly connected with a number of data mining problems. One of those is also an inherently important task in agriculture: yield prediction. Given a yield prediction model, which of the predicto...

Optimal Spatial Prediction Using Ensemble Machine Learning.

Spatial prediction is an important problem in many scientific disciplines. Super Learner is an ensemble prediction approach related to stacked generalization that uses cross-validation to search for the optimal predictor amongst all convex combinations of a heterogeneous candidate set. It has been applied to non-spatial data, where theoretical results demonstrate it will perform asymptotically ...

Fast Numerical and Machine Learning Algorithms for Spatial Audio Reproduction

Title of dissertation: FAST NUMERICAL AND MACHINE LEARNING ALGORITHMS FOR SPATIAL AUDIO REPRODUCTION Yuancheng Luo, Doctor of Philosophy, 2014 Dissertation directed by: Professor Ramani Duraiswami Department of Computer Science Audio reproduction technologies have underwent several revolutions from a purely mechanical, to electromagnetic, and into a digital process. These changes have resulted ...