A machine learning approach for coconut sugar quality assessment and prediction

• Main Authors: Alonzo, Lea Monica B., Chioson, Francheska B., Co, Homer S., Bugtai, Nilo T., Baldovino, Renann G.
• Format: text
• Published: Animo Repository 2019
• Subjects: Machine learning; Sugar—Quality control; Manufacturing
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2774
• Institution: De La Salle University

This study presents a machine learning approach to accurately assess the quality of coconut sugar using RGB values. Python and scikit-learn were used to run the following machine learning algorithms: artificial neural network (ANN), stochastic gradient descent (SGD), k-nearest neighbors (k-NN) algor...