论文标题
分布数据的判别分析
Discriminant Analysis of Distributional Data viaFractional Programming
论文作者
论文摘要
我们解决分布数据的分类，其中单位通过直方图或间隔值变量描述。所提出的方法使用线性判别函数，其中分布或间隔在特定假设下由分位数函数表示。此判别函数允许以分位数函数的形式定义每个单元的分数，该分位数函数用于使用Mallows距离将单位分类为两个先验组。提议的线性判别方法有多种应用领域。在这项工作中，我们使用全年的战斗将根据空中时间和到达/出发延误对在纽约机场运营的航空公司进行分类。
We address classification of distributional data, where units are described by histogram or interval-valued variables. The proposed approach uses a linear discriminant function where distributions or intervals are represented by quantile functions, under specific assumptions. This discriminant function allows defining a score for each unit, in the form of a quantile function, which is used to classify the units in two a priori groups, using the Mallows distance. There is a diversity of application areas for the proposed linear discriminant method. In this work we classify the airline companies operating in NY airports based on air time and arrival/departure delays, using a full year fights.
