摘要
创新能力研究一直是学者们关注的热点问题。支持向量机是以统计学习理论为依据,发展起来的一种新的机器学习方法,在解决小样本、非线性及高维模式识别问题中表现出许多特有的优势。通过建模和实证,尝试将支持向量机引入企业产品创新能力评价领域,并与BP神经网络评价方法相比较,从而发现其优越性。
The creativity has long been a research focus for scholars. Based on Statistical Learning Theory, Support Vector Machines （SVM） is a new kind of machine study method with typical advantages. By setting up the model and providing substantial evidence, this paper adopts Support Vector Machines to evaluate enterprise＇s product innovative ability, and compares with the BP Neural Network, then reveals its superiority.
