基于似然损失函数的组样本排序学习方法
发布时间：2018-10-19 09:51
【摘要】：组样本用于模型训练,为排序学习方法的构造提供一种新的思路.文中改进已有的组样本排序学习方法,构造组样本损失函数,用于排序学习模型的训练.基于似然损失函数,采用样本偏序权重损失函数和最优初始序列选择方法,构造基于神经网络的组排序学习方法,实验证明文中方法能够有效提高排序准确率.
[Abstract]:Group samples are used for model training, which provides a new idea for the construction of ranking learning methods. In this paper, we improve the existing group sample sorting learning method and construct the group sample loss function, which can be used to train the sorting learning model. Based on likelihood loss function, sample partial order weight loss function and optimal initial sequence selection method are used to construct group ranking learning method based on neural network. The experimental results show that the proposed method can effectively improve the accuracy of sorting.
【作者单位】： 大连理工大学人文与社会科学学部;大连理工大学计算机科学与技术学院;
【基金】：国家自然科学基金项目(No.61602078,61572102,61402075,61277370) 中国博士后科学基金项目(No.2016T90224,2015M581337) 中央高校基本科研业务费专项资金(No.DUT15RW401)资助~~
【分类号】：TP391.3;TP181
本文编号：2280780
[Abstract]:Group samples are used for model training, which provides a new idea for the construction of ranking learning methods. In this paper, we improve the existing group sample sorting learning method and construct the group sample loss function, which can be used to train the sorting learning model. Based on likelihood loss function, sample partial order weight loss function and optimal initial sequence selection method are used to construct group ranking learning method based on neural network. The experimental results show that the proposed method can effectively improve the accuracy of sorting.
【作者单位】： 大连理工大学人文与社会科学学部;大连理工大学计算机科学与技术学院;
【基金】：国家自然科学基金项目(No.61602078,61572102,61402075,61277370) 中国博士后科学基金项目(No.2016T90224,2015M581337) 中央高校基本科研业务费专项资金(No.DUT15RW401)资助~~
【分类号】：TP391.3;TP181
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