机译:K-Collest邻居生存概率预测方法
RAND Corporation Santa Monica CA 90407 United States;
Sauder School of Business University of British Columbia Vancouver BC V6T 1Z2 Canada;
School of Management Yale University New Haven CT 06520 United States;
Division of Biostatistics UCSF San Francisco CA 94107 United States;
University of Chicago Medical Center Chicago IL 60637 United States;
University of Chicago Medical Center Chicago IL 60637 United States;
Graduate School of Business Stanford University Stanford CA 94305 United States;
Cox regression; K-nearest neighbors; Kaplan-Meier; Mahalanobis distance; Nonparametric survival analysis; Organ transplantation; Right-censored data; Survivor function;
机译:K近邻生存概率预测方法
机译:通过传统井日志和核心数据集成升级分层聚类和k最近邻的磁化性预测的电缆日志分析介绍
机译:基于支持向量机和K最近邻方法的土壤污染程度预测:以伊朗阿拉克为例
机译:使用特征选择方法增强K最近邻分类器对糖尿病的预测性能
机译:关于K近邻法生成大学生成绩预测的模糊规则。
机译:用于风险分类和生存概率预测的无模型机器学习方法
机译:利用K-Collect邻(KNN)方法的SUMO应用程序的流量预测