The Strength of Weak Learnability
Machine Learning
Cryptographic limitations on learning Boolean formulae and finite automata
Journal of the ACM (JACM)
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Strategies for combining classifiers employing shared and distinct pattern representations
Pattern Recognition Letters - special issue on pattern recognition in practice V
Validation of voting committees
Neural Computation
Multiclass Boosting for Weak Classifiers
The Journal of Machine Learning Research
Hierarchical classifier with overlapping class groups
Expert Systems with Applications: An International Journal
Hierarchical Nonlinear Approximation for Experimental Design and Statistical Data Fitting
SIAM Journal on Scientific Computing
The Journal of Machine Learning Research
Neural Systems for Short-Term Forecasting of Electric Power Load
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
On cluster validity for the fuzzy c-means model
IEEE Transactions on Fuzzy Systems
A validity criterion for fuzzy clustering
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part I
New specifics for a hierarchial estimator meta-algorithm
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
| Hi-index | 12.05 |
In this paper, a new machine learning solution for function approximation is presented. It combines many simple and relatively inaccurate estimators to achieve high accuracy. It creates - in incremental manner - hierarchical, tree-like structure, adapting it to the specific problem being solved. As most variants use the errors of already constructed parts to direct further construction, it may be viewed as example of boosting - as understood in general sense. The influence of particular constituent estimator on the whole solution's output is not constant, but depends on the feature vector being evaluated. Provided in this paper are: general form of the metaalgorithm, a few specific, detailed solutions, theoretical basis and experimental results with one week power load prediction for country-wide power distribution grid and on simple test datasets.