Pumpkin Seeds Classification: Artificial Neural Network and Machine Learning Methods
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Abstract
Pumpkin seeds may be small, but they're packed with valuable nutrients. Eating just a small amount can provide a significant amount of healthy fats, magnesium and zinc. For this reason, pumpkin seeds are associated with various health benefits. These include improving heart health, prostate health, and protection against certain cancers. In addition, these seeds are easy to incorporate into the diet. The main objective of this research is to design and implement an artificial neural network model, and the machine learning models, i.e., LR, SVM, DT, Naive Bayes, and K-NN, were investigated for their accuracy, precision, and recall on 2500 samples obtained from Kaggle. The average accuracy of LR, SVM, DT, Naive Bayes and K-NN were 99.81%, 48.00%, 100.00%, 95.80%, 46.60% and 77.20%, respectively. Thus, it was found that the decision tree model performed better than the other models. The proposed model can be effectively used for characterization, classification and identification of pumpkin seeds.
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