Application of K-Means and Fuzzy K-Means to Rice Dataset in Sierra Leone
By: R. M. Bangura, S. D. Johnson and O. Mbulayi
Open Access
|Dec 2020Abstract
As k-means and fuzzy k-means are regarded as unsupervised dimensional reduction learning techniques, we present an application of this technique from the Agronomic data collected in 2015 to demonstrate the efficiency of fuzzy k means over k means of eight different types of rice varieties in Sierra Leone. Also, we identified different rice varieties as outliers from the silhouette clusters (segment).
DOI: https://doi.org/10.4038/sljastats.v21i3.8062 | Journal eISSN: 2424-6271
Language: English
Page range: 69 - 73
Published on: Dec 31, 2020
Published by: The Institute of Applied Statistics, Sri Lanka
In partnership with: Paradigm Publishing Services
© 2020 R. M. Bangura, S. D. Johnson, O. Mbulayi, published by The Institute of Applied Statistics, Sri Lanka
This work is licensed under the Creative Commons License.