Publication Type : Conference Proceedings
Publisher : Springer
Source : Intelligent Systems and Sustainable Computing
Url : https://link.springer.com/chapter/10.1007/978-981-99-4717-1_14
Campus : Bengaluru
School : School of Engineering
Year : 2023
Abstract : Image classification is the most accurate way to anticipate a classifier’s accuracy. Categorization approaches include logistic regression, K-nearest neighbors, Naive Bayes, decision trees, and support vector machines. Artificial neural networks and convolutional neural networks can also be used for classification. The best classification algorithm is predicted using K-nearest neighbors (KNN) and support vector machines (SVM). The “Cats versus Dogs” dataset and the “Human and Animals” dataset are used to test the accuracy in this research.
Cite this Research Publication : Marri, S.P., Nikith, B.V., Keerthan, N.K.S., Jayan, S., SVM Versus KNN: Prediction of Best Image Classifier, Smart Innovation, Systems and Technologies 363, pp. 147-157 (2023)