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.