Support vector machines (SVMs) are initially designed for binary classification. How to effectively extend them for multiclass classification is still an ongoing research topic. A multiclass classifier is constructed by combining SVM//g/" algorithm with directed acyclic graph SVM (DAGSVM) method, named DAGSVM/zgA/. A new method is proposed to select theworkingsetwhichisidenticaltotheworkingsetselectedbySVMhght approach.Experimentalresultsindicate DAGSVMlightis competitive with DAGSMO. It is more suitable for practice use. It may be an especially useful tool for large-scale multiclass classification problems and lead to more widespread use of SVMs in the engineering community due to its good performance.