- When the data is outlier free and clean then go for SVM. If your data might contain outliers then Random forest would be the best choice.
- Generally, SVM consumes more computational power than Random Forest, so if you are constrained with memory go for Random Forest machine learning algorithm.
- Random Forest gives you a very good idea of variable importance in your data, so if you want to have variable importance then choose Random Forest machine learning algorithm.
- Random Forest machine learning algorithms are preferred for multiclass problems.
- SVM is preferred in multi-dimensional problem set - like text classification.