| In the past years , computer techniques especially of database tech -niques have developed greatly, area of people' s activities has been extended, rhythm of life has speeded up. People are able to get and store data more quickly, easily and cheaply, which make the data and information increase exponentially . Facing the great capacity of data , people are under the pressure of information explosion and data glut . It will be garbage if the massive data can't be exploited. It' s the knowledge that has great effect on the development of society. Data mining is a technology that finds understand rules and extracts valuable knowledge.There are lots of branches in data mining , one of them is classification rules mining. With proper training algorithm on training data, it will generate classifiers that could get prediction to unknown examples . Support vector machine(SVM)is a new classification algorithm based on statistical learning theory. Compared to other classifiers, SVM has better generalization performance and higher prediction accuracy to test example .So SVM has had a lot of application.Naive SVM is only able to deal with binary classification . In this thesis , after discussed the current multiclass SVMs , a novel multiclass SVM classifier based on distance is proposed. I give a new algorism and through experiment test it validity. |
