K-means cluster analysis of the West African species of cereals based on nutritional value composition

K-means cluster analysis of the West African species of cereals based on nutritional value composition

Author: 
Atsa'am, Donald Douglas
Publisher: 
Rural Outreach Programme (ROP)
Date published: 
2021
Record type: 
Responsibility: 
Oyelere, Solomon, jt. author
Balogun, Oluwafemi Samson, jt. author
Wario, Ruth, jt. author
Blamah, NV, jt. author
Journal Title: 
African Journal of Food, Agriculture, Nutrition and Development
Source: 
African Journal of Food, Agriculture, Nutrition and Development, Vol 21, No. 1, January 2021, pp. 17195-17212
Abstract: 

The K-means algorithm was deployed to extract clusters within the prevalent cereal foods in West Africa. The West Africa Food Composition Table (WAFCT) presents all the 76 food sources in the cereals class as a single group without considering the similarity or dissimilarity in nutritional values. Using K-means clustering, the Euclidean distance between nutritional values of all cereal food items were measured to generate six sub-groups based on similarity. A one-way analysis to validate the results of the extracted clusters was carried out using the mean square values. For every nutrient, the "within groups" and "between groups" values of the mean squares were examined. This was done to ascertain how similar or dissimilar data points in the same or different clusters were to each other. It was discovered that the P values for all "between groups" and "within groups" mean squares for every nutrient was P

Language: 

CITATION: Atsa'am, Donald Douglas. K-means cluster analysis of the West African species of cereals based on nutritional value composition . : Rural Outreach Programme (ROP) , 2021. African Journal of Food, Agriculture, Nutrition and Development, Vol 21, No. 1, January 2021, pp. 17195-17212 - Available at: https://library.au.int/k-means-cluster-analysis-west-african-species-cereals-based-nutritional-value-composition