Comparison on Classification Performance Between Random Forests and Support Vector Machine
Weixiong Zha · IEEE Software · 2012
Random Forests is an excellent classifier.In order to make Chinese scholars fully understand its performance,this paper compared it with Support Vector Machine widely used in China by means of data experiments to objectively show its classification performance.The experiments,using 20 UCI data sets,were carried out from three main aspects:generalization,noise robustness and imbalanced data classification.Experimental results can provide references for classifiers'choice and use.