Attributes of the performance of central processing units: a relative performance prediction model
Communications of the ACM
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Neural networks and the bias/variance dilemma
Neural Computation
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Backpropagation in Decision Trees for Regression
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
New Measure of Classifier Dependency in Multiple Classifier Systems
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
SVMTorch: support vector machines for large-scale regression problems
The Journal of Machine Learning Research
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
The Knowledge Engineering Review
Genetic programming in classifying large-scale data: an ensemble method
Information Sciences: an International Journal - Special issue: Soft computing data mining
Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods
The Journal of Machine Learning Research
A novel grammar-based genetic programming approach to clustering
Proceedings of the 2005 ACM symposium on Applied computing
Combination of Multi Level Forecasts
Journal of VLSI Signal Processing Systems
The Dynamics of Negative Correlation Learning
Journal of VLSI Signal Processing Systems
Machine Learning: An Algorithmic Perspective
Machine Learning: An Algorithmic Perspective
Genetic algorithms in classifier fusion
Applied Soft Computing
Artificial Intelligence in Medicine
Pooling for Combination of Multilevel Forecasts
IEEE Transactions on Knowledge and Data Engineering
Using genetic programming to obtain implicit diversity
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Ensemble techniques for parallel genetic programming based classifiers
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
A Generic Multilevel Architecture for Time Series Prediction
IEEE Transactions on Knowledge and Data Engineering
Fuzzy basis functions, universal approximation, and orthogonal least-squares learning
IEEE Transactions on Neural Networks
Local and global optimization for Takagi-Sugeno fuzzy system by memetic genetic programming
Expert Systems with Applications: An International Journal
A fuzzy evolutionary framework for combining ensembles
Applied Soft Computing
Performance evaluation of microbial fuel cell by artificial intelligence methods
Expert Systems with Applications: An International Journal
Novel multiclass classification for home-based diagnosis of sleep apnea hypopnea syndrome
Expert Systems with Applications: An International Journal
| Hi-index | 12.06 |
This work presents the GRADIENT (GRAmmar-DrIven ENsemble sysTem) framework for the generation of hybrid multi-level predictors for function approximation and regression analysis tasks. The proposed model uses a context-free grammar guided genetic programming for the automatic building of multi-component prediction systems with hierarchical structures. A multi-population evolutionary algorithm together with resampling and cross-validatory approaches are used to increase component models' diversity and facilitate more robust and efficient search for accurate solutions. The system has been tested on a number of synthetic and publicly available real-world regression and time series problems for a range of configurations in order to identify and subsequently illustrate and discuss its characteristics and performance. GRADIENT has been shown to be very competitive and versatile when compared to a number of state-of-the-art prediction methods.