Random Forest Svm Comparison. Random Forest supports multiclass classificationwhereas SVM needs multiple models for the same. Comparison of machine learning algorithms random forest artificial neural network and support vector machine to maximum likelihood for supervised crop type classification.
Comparison of Random Forest k-Nearest Neighbor and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery December 2017 Sensors 18118. An empirical comparison of supervised learning algorithms. Statnikov A Wang L Aliferis CF.
For multiclass problem you will need to reduce it into multiple binary classification problems.
An empirical comparison of supervised learning algorithms. However I think in general random forests do better than SVM or Neural Net in terms of prediction accuracy. Random Forest is intrinsically suited for multiclass problems while SVM is intrinsically two-class. Up to 10 cash back The comparison of different classifiers indicates that random forestferns outperform the SVM in terms of time consumption.