In order to improve the generalization ability of binary decision trees, a new learning algorithm, the MMDT algorithm, is presented. Based on statistical learning theory the generalization performance of binary decisi...In order to improve the generalization ability of binary decision trees, a new learning algorithm, the MMDT algorithm, is presented. Based on statistical learning theory the generalization performance of binary decision trees is analyzed, and the assessment rule is proposed. Under the direction of the assessment rule, the MMDT algorithm is implemented. The algorithm maps training examples from an original space to a high dimension feature space, and constructs a decision tree in it. In the feature space, a new decision node splitting criterion, the max-min rule, is used, and the margin of each decision node is maximized using a support vector machine, to improve the generalization performance. Experimental results show that the new learning algorithm is much superior to others such as C4. 5 and OCI.展开更多
In this paper, I carried on the research under the guidance of the theory of hierarchy of needs, and preventing a detailed work plan. During the research, we cleared for measures, which were ＂adhere to the people-ori...In this paper, I carried on the research under the guidance of the theory of hierarchy of needs, and preventing a detailed work plan. During the research, we cleared for measures, which were ＂adhere to the people-oriented, mining the potential of students, make up the insufficient to properly resolve the crisis, to create a learning atmosphere＂. So it provides a new idea for promoting the construction and development of college student cadres, and maintains the stability of the campus and the construction of harmonious campus.展开更多
文摘In order to improve the generalization ability of binary decision trees, a new learning algorithm, the MMDT algorithm, is presented. Based on statistical learning theory the generalization performance of binary decision trees is analyzed, and the assessment rule is proposed. Under the direction of the assessment rule, the MMDT algorithm is implemented. The algorithm maps training examples from an original space to a high dimension feature space, and constructs a decision tree in it. In the feature space, a new decision node splitting criterion, the max-min rule, is used, and the margin of each decision node is maximized using a support vector machine, to improve the generalization performance. Experimental results show that the new learning algorithm is much superior to others such as C4. 5 and OCI.
文摘In this paper, I carried on the research under the guidance of the theory of hierarchy of needs, and preventing a detailed work plan. During the research, we cleared for measures, which were ＂adhere to the people-oriented, mining the potential of students, make up the insufficient to properly resolve the crisis, to create a learning atmosphere＂. So it provides a new idea for promoting the construction and development of college student cadres, and maintains the stability of the campus and the construction of harmonious campus.
