中文摘要：

本文基于中药药理文献数据，以中药的药性、药味、毒性、归经、主治、功效6个属性的所有值作为属性集，使用支持向量机对187个中药药理作用分别构建预测模型，并使用交叉验证的方法确定模型预测的准确率。然后使用准确率大于90%的中药药理作用预测模型对《中国药典》（2010版）收录的624味中药进行药理作用的预测。结果发现有108个模型的准确率大于90%，而抗菌作用预测模型的准确率达到99.76%。对中药的预测中预测百分比最高的是北豆根的抗氧化作用。

英文摘要：

B ased on Chinese medicine pharmacological literature data , the property , flavor , toxicity , meridian tropism, efficacy, and clinical application of Chinese herbal medicine were used as a set of attributes. The sup-port vector machine （ SVM ） was used in the establishment of predictive models of 187 pharmacological effects of Chinese herbal medicine respectively. And the cross-validation method was used to determine the accuracy of predictive models . After that , the predictive models with the predictive accuracy rate greater than 90% were used to predicate pharmacological effects of 624 herbals recorded in the Chinese Pharmacopoeia（2010 edition）. It was found that the accuracy rate of 108 models was greater than 90%, and the accuracy rate of antibacterial effect predictive model was 99.76%. The highest predictive value of Chinese herbal medicine was the anti-oxi-dation effect of Menispermi Rhizoma.