Difference between support vector machine and random forest


I would just like to ask what’s the main difference between svm and random forest in terms of their classification accuracy?

Is there is a better algorithm among the two given a certain condition?


I’d recommend using the RF model. In theory, SVM might give better results on some sites, but it’s much slower and got less testing.

Ok thank you very much.



Small complement on that. The results of the benchmarking phase of the Sen2-Agri project showed that Random Forest algorithm performs generally better than the Support Vector Machine. However, classes with very few training samples can be better recognized by the SVM algorithm.