# A Genetic Algorithm-Based, Hybrid Machine Learning Approach to Model Selection

@article{Bies2006AGA, title={A Genetic Algorithm-Based, Hybrid Machine Learning Approach to Model Selection}, author={Robert R Bies and Matthew F. Muldoon and Bruce G. Pollock and Stephen B. Manuck and Gwenn S. Smith and Mark E. Sale}, journal={Journal of Pharmacokinetics and Pharmacodynamics}, year={2006}, volume={33}, pages={195-221} }

We describe a general and robust method for identification of an optimal non-linear mixed effects model. This includes structural, inter-individual random effects, covariate effects and residual error models using machine learning. This method is based on combinatorial optimization using genetic algorithm.

## 97 Citations

### Generalized Net model of selection operator of genetic algorithms

- Computer Science2010 5th IEEE International Conference Intelligent Systems
- 2010

The apparatus of Generalized Nets is applied here to a description of a selection operator, which is one of the basic genetic algorithm operators. This genetic operator performs a probabilistic…

### A genetic algorithm based global search strategy for population pharmacokinetic/pharmacodynamic model selection

- BiologyBritish journal of clinical pharmacology
- 2015

These methods are reviewed, with emphasis on genetic algorithm approaches, and the role these methods may play in population pharmacokinetic/pharmacodynamic model selection is discussed.

### Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building

- BiologyJournal of Pharmacokinetics and Pharmacodynamics
- 2012

The single-objective, hybrid genetic algorithm represents a general pharmacokinetics model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data.

### Population pharmacokinetic model selection assisted by machine learning

- Computer Science, BiologyJournal of pharmacokinetics and pharmacodynamics
- 2021

This manuscript compared the classical pharmacometric approach with two machine learning methods, genetic algorithm and neural networks, in different scenarios based on simulated pharmacokinetic data, and suggested that machine learning approaches can achieve a first fast selection of models which can be followed by more conventional pharmacometric approaches.

### Generalized Net Models of Basic Genetic Algorithm Operators

- Computer ScienceImprecision and Uncertainty in Information Representation and Processing
- 2016

Generalized nets (GN) are applied here to describe some basic operators of genetic algorithms, namely selection, crossover and mutation and different functions for selection (roulette wheel selection…

### Developing an adaptation process for real-coded genetic algorithms

- Computer ScienceComput. Syst. Sci. Eng.
- 2020

Experimental results show that this new process accelerated the algorithm and a certain solution has been reached in fewer generations, and better solutions were achieved, especially for a certain number of generations.

### Identification of Optimal Kernel Parameters of RKHS model based on Genetics Algorithm

- Computer Science
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This paper proposes a new approach based on the Genetics Algorithm to determine the optimal kernel parameters of the Reproducing Kernel Hilbert Space (RKHS) model. These parameters are the width of…

### Probability Estimation by an Adapted Genetic Algorithm in Web Insurance

- Computer ScienceLION
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This work proposes to use a genetic algorithm specifically adapted to overcome the statistical method defaults and shows its performances on real datasets provided by the company MeilleureAssurance.com.

### An Evolutionary Search Algorithm for Covariate Models in Population Pharmacokinetic Analysis.

- BiologyJournal of pharmaceutical sciences
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### Modelling of a Roulette Wheel Selection Operator in Genetic Algorithms Using Generalized Nets

- Computer Science
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The apparatus of Generalized Nets (GN) is applied here to a description of a selection operator, which is one of the basic genetic algorithm operators. The GN model presented here describes roulette…

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