Buscar
Mostrando ítems 21-30 de 4399
A new supervised learning algorithm inspired on chemical organic compounds
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2013)
In this work, a new supervised learning method called artificial organic networks is proposed for modeling problems, i.e. fitting, analyzing, inference and classification. In fact, this technique is inspired on chemical ...
An approach to train machine leaning algorithms
(Universidad de San Andrés. Departamento de Economía, 2020-11)
With the evolution of data mining the trend is to train more complex algorithms. Those sophisticated machine learning algorithms are being used in several fields to take important decisions. Examples in economics include ...
Adaptive hierarchical censored production rule-based system: A genetic algorithm approach
(1996-01-01)
An adaptive system called GBHCPR (Genetic Based Hierarchical Censored Production Rule) system based on Hierarchical Censored Production Rule (HCPR) system is presented that relies on development of some ties between Genetic ...
Extreme learning machine adapted to noise based on optimization algorithms
(IOP Publishing, 2020)
The extreme learning machine for neural networks of feedforward of a single hidden layer randomly assigns the weights of entry and analytically determines the weights the output by means the Moore-Penrose inverse, this ...
Supporting academic decision making at higher educational institutions using machine learning-based algorithms
Decisions made by deans and university managers greatly impact the entire academic community as well as society as a whole. In this paper, we present survey results on which academic decisions they concern and the variables ...
Uncertainty Propagation in Fuzzy Grey Cognitive Maps With Hebbian-Like Learning Algorithms
This paper is focused on an innovative fuzzy cognitive maps extension called fuzzy grey cognitive maps (FGCMs). FGCMs are a mixture of fuzzy cognitive maps and grey systems theory. These have become a useful framework for ...
Automatic Design of Decision-Tree Algorithms with Evolutionary Algorithms
(Mit Press, 2013-11-01)
This study reports the empirical analysis of a hyper-heuristic evolutionary algorithm that is capable of automatically designing top-down decision-tree induction algorithms. Top-down decision-tree algorithms are of great ...
Otimização de hiperparâmetros em machine learning utilizando uma surrogate e algoritmos evolutivos
(Universidade Tecnológica Federal do ParanáCornelio ProcopioBrasilEngenharia da ComputaçãoUTFPR, 2020-07-16)
This work presents a new approach for hyperparameter optimization in Machine Learning algorithms. The idea is to build a surrogate with quasirandom numbers generated by Sobol's algorithm and then use an evolutionary algorithm ...