Abstract A dynamic programming algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data ...
- This paper presents a learning approach using cerebellar model articulation controller (CMAC) to accommodate faults for a class of multivariable nonlinear systems. A CMAC is prop...
Chih-Min Lin, Chang-Chih Chung, Yu-Ju Liu, Daniel ...
We propose two new improvements for bagging methods on evolving data streams. Recently, two new variants of Bagging were proposed: ADWIN Bagging and Adaptive-Size Hoeffding Tree (...
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer...
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Learning curves for Gaussian process (GP) regression can be strongly affected by a mismatch between the ‘student’ model and the ‘teacher’ (true data generation process), e...