The need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. Many of these applications naturally involve temporal data...
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
To facilitate more meaningful interpretation considering the internal interdependency relationships between data values, a new form of high-order (multiple-valued) pattern known a...
This paper presents a novel approach to financial time series analysis and prediction. It is mainly devoted to the problem of forecasting university facility and administrative co...
Tomasz G. Smolinski, Darrel L. Chenoweth, Jacek M....
Often remote investigations use autonomous agents to observe an environment on behalf of absent scientists. Predictive exploration improves these systems’ efficiency with onboa...