We have developed and tested a genetic algorithm (GA) for pattern recognition, which identifies molecular descriptors that optimize the separation of the activity classes of olfactory stimulants in a plot of the two or three largest principal components of the data. Because principal components ...
(LDA).First,normalization and gene filtering are used to pre-process dataset.Then genetic algorithm is performed to select the best features.We use linear discriminant analysis to form the fitness function.In the experiments,a good gene subset is obtained based on the global searching of ...
Kumar, S., Sahoo, G. (2015). Classification of Heart Disease Using Naïve Bayes and Genetic Algorithm. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 2. Smart Innovation, Systems and Technologies, vol 32. Springer, New ...
by reducing the number of factors, such as environmental variables, or dynamicmicrobial interactions, and to increase theinterpretabilityof the classification models.Genetic algorithmuses computational simulations of evolutionary processes to explore highly fit models; RF is efficient but may not be as fl...
The maximum relevance minimum redundancy (mRMR) is applied to pre-evaluate features with discriminative information while genetic algorithm (GA) is utilized to find the optimized feature subsets. SVM is used for the construction of classification models. The overall accuracy with three-layer predictor ...
A way to overcome this trouble consists on using any method able to scale-down the dimensionality of the problem and/or to reduce the complexity of the machine learning models. In this paper, we propose the use of a multiobjective genetic algorithm to minimize both the dimension of the ...
visualization nlp data-science machine-learning statistics computer-vision deep-learning clustering interpolation genetic-algorithm linear-algebra regression nearest-neighbor-search classification wavelet dataframe computer-algebra-system manifold-learning multidimensional-scaling llm Updated Mar 23, 2025 Java time...
Using an approach similar to the biological processes of natural selection and evolution, the genetic algorithm (GA) is a nonconventional optimum search technique. Genetic algorithms have the ability to search large and complex decision spaces and handle nonconvexities. In this paper, the GA is app...
This tutorialis prepared based on a previous version of the project but it still a good resource to start with coding the genetic algorithm. Tutorial: Introduction to Genetic Algorithm Get started with the genetic algorithm by reading the tutorial titledIntroduction to Optimization with Genetic Algorit...
4 Convergence of genetic algorithm in the configuration space. a, Genetic algorithm convergence for the six major Boolean logic gates at 77 K. The best fitness of the 20 genomes is plotted against generation. b, Histograms of the control voltages that configure the dopant network to the XNOR ...