A Performance Comparison of Three Machine Learning Algorithms for Leaf Recognition using the Text-Based Dataset
Phuc Hong Ngo ’23, Can Tho City, Vietnam
Majors: Computer Science; Math
Machine learning is widely used for classification in various fields. In this research, we compared and analyzed the performance of three popular machine learning classifiers such as KNN, SVM, and ANN, using the leaf dataset. The original dataset was preprocessed, and the feature selection technique was used to divide the preprocessed dataset into two different types of the dataset. According to experiments, the ANN classifier showed 76.18% of accuracy when all the features were employed, and it outperformed other classifiers. However, when partial features were employed, the SVM classifier showed 73.31% of accuracy that outperformed other classifiers.