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Found 13 papers, 4 papers with code
HYB-PARSIMONY: A hybrid approach combining Particle Swarm Optimization and Genetic Algorithms to find parsimonious models in high-dimensional datasets
In the early stages of the optimization process, GA methods have a preponderance to accelerate the search for parsimony.
PSO-PARSIMONY: A method for finding parsimonious and accurate machine learning models with particle swarm optimization. Application for predicting force–displacement curves in T-stub steel connections
We present PSO-PARSIMONY, a new methodology to search for parsimonious and highly accurate models by means of particle swarm optimization.
Artificial Intelligence Models for Assessing the Evaluation Process of Complex Student Projects
The evaluation of student projects is a difficult task, especially when they involve both a technical and a creative component.
An advanced methodology to enhance energy efficiency in a hospital cooling-water system
This process consisted of searching for low-complexity models using a methodology called GAparsimony.
A comparative study of six model complexity metrics to search for parsimonious models with GAparsimony R Package
Nowadays, interest is growing in automating KDD processes.
Parsimonious Modelling for Estimating Hospital Cooling Demand to Improve Energy Efficiency
Of all the different types of public buildings, hospitals are the biggest energy consumers.
Hybrid methodology based on Bayesian optimization and GA-PARSIMONY to search for parsimony models by combining hyperparameter optimization and feature selection
This article presents a hybrid methodology that combines Bayesian optimization (BO) with a constrained version of the GA-PARSIMONY method to obtain parsimony models.
Stacking ensemble with parsimonious base models to improve generalization capability in the characterization of steel bolted components
To this end, a database with the results of a set of finite element (FE) simulations, which represent real responses of bolted components, is utilized to create a stacking ensemble model that combines the predictions of different parsimonious base models.
Evaluation of a novel GA-based methodology for model structure selection: The GA-PARSIMONY
The most basic IBk, ridge regression (LIN) and M5P were only classified as winner models in the simpler databases, but using less number of features in those cases (up to a 20–25% of the initial inputs).
Improving hotel room demand forecasting with a hybrid GA-SVR methodology based on skewed data transformation, feature selection and parsimony tuning
This article presents a hybrid methodology in which a KDD scheme is optimized to build accurate parsimonious models.
Searching parsimonious solutions with GA-PARSIMONY and XGboost in high-dimensional databases
The methodology was designed to optimize the search of parsimonious models by feature selection, parameter tuning and model selection.
GA-PARSIMONY: A GA-SVR approach with feature selection and parameter optimization to obtain parsimonious solutions for predicting temperature settings in a continuous annealing furnace
To this end, a novel GA selection procedure is introduced based on separate cost and complexity evaluations.
A numerical-informational approach for characterising the ductile behaviour of the T-stub component. Part 2: Parsimonious soft-computing-based metamodel
The accuracy of the component-based method relies heavily on the characteristic response of their constitutive elements.
