基于混合特征预测药物-靶标相互作用的K近邻模型

K-nearest neighbor model for predicting drug-target interaction based on hybrid features

针对核受体数据提取药物-靶标之间的混合特征,使用K近邻算法进行预测。对精确率、召回率、F1值等评价指标与其他算法进行了比较,验证模型的预测性能。

With the nuclear receptor dataset,a K-nearest neighbor prediction model is used to extract the drug-target interaction hybrid features.The method is compared with other algorithms in terms of precision,recall,and F1-score to evaluate the prediction property of the model.