A hybrid approach using genetic algorithm with k-means in clustering of Indian mustard genotypes
Author(s): Hemant Poonia, Ramavtar, BK Hooda and Ramniwas
Abstract: The study was carried out to check the
applicability of a hybrid approach using a Genetic Algorithm with K-means for
clustering of Indian mustard genotypes. The secondary data on growth and yield
attributes of 80 Indian mustard genotypes was used for the identification of
patterns and best genotypes for plant breeders. A hybrid clustering method was used for getting improved clusters by
combining two clustering methods genetic algorithm and k-means. Initially,
cluster centres were obtained using the genetic algorithm clustering method,
and then cluster centres were used as input for the k-means procedure. The
cluster’s quality was measured in terms of the total within the sum of
squares and the sum of squares ratio. It was concluded that an improved cluster can be obtained if the
hybrid clustering method is applied to the subset of selected variables.
Hemant Poonia, Ramavtar, BK Hooda, Ramniwas. A hybrid approach using genetic algorithm with k-means in clustering of Indian mustard genotypes. Int J Stat Appl Math 2025;10(3):93-96. DOI: 10.22271/maths.2025.v10.i3b.2010
