Related Experiment Video
Updated: Jul 7, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
Published on: December 7, 2021
Genetic algorithms for generation of class boundaries
S K Pal1, S Bandyopadhyay, C A Murthy
1Machine Intelligence Unit, Indian Stat. Inst., Calcutta.
Abstract:
A method is described for finding decision boundaries, approximated by piecewise linear segments, for classifying patterns in R(N),N>/=2, using an elitist model of genetic algorithms. It involves generation and placement of a set of hyperplanes (represented by strings) in the feature space that yields minimum misclassification. A scheme for the automatic deletion of redundant hyperplanes is also developed in case the algorithm starts with an initial conservative estimate of the number of hyperplanes required for modeling the decision boundary. The effectiveness of the classification methodology, along with the generalization ability of the decision boundary, is demonstrated for different parameter values on both artificial data and real life data sets having nonlinear/overlapping class boundaries. Results are compared extensively with those of the Bayes classifier, k-NN rule and multilayer perceptron.
Related Concept Videos
Evolutionary Relationships through Genome Comparisons
Genetic Screens
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Genetic Drift
Mutation, Gene Flow, and Genetic Drift
Genetics of Speciation
Hybrid Zones