Comparison Between Svm And Ann. Classification of microcalcification clusters from mammograms plays essential roles in computer-aided diagnosis for early detection of breast cancer where support vector machine SVM and artificial neural network ANN are two commonly used techniques. For ANN there is no significant difference between the one-against-all method and a simple 11-output method.
Classification result is obtained from the model that has been tested. Based on this study we conclude that the ANN classifier is better than SVM for the EEG drowsiness signals when using one EEG channel. Comparing SVM and ANN based Machine Learning Methods for Species Identification of Food Contaminating Beetles Abstract.
Our results have also confirmed some potential limitations of both models which have been rarely discussed in the sentiment classification literature like the computational cost of SVM at the running time and ANN at the training time.
You can use both ANN and SVM. Begingroup From what I know multilayer feedforward ANN are universal approximators more or less irrespective of the activation function. I am not aware of a similar result for SVM which dependto my knowledge much more on the kernel function used. You can use both ANN and SVM.
