Weighted Distance Weighted Discrimination and Its Asymptotic Properties
نویسندگان
چکیده
منابع مشابه
Weighted Distance Weighted Discrimination and Its Asymptotic Properties.
While Distance Weighted Discrimination (DWD) is an appealing approach to classification in high dimensions, it was designed for balanced datasets. In the case of unequal costs, biased sampling, or unbalanced data, there are major improvements available, using appropriately weighted versions of DWD (wDWD). A major contribution of this paper is the development of optimal weighting schemes for var...
متن کاملAsymptotic Properties of Distance-Weighted Discrimination
While Distance-Weighted Discrimination (DWD) is an appealing approach to classification in high dimensions, it was designed for balanced data sets. In the case of unequal costs, biased sampling or unbalanced data, there are major improvements available, using appropriately weighted versions of DWD. A major contribution of this paper is the development of optimal weighting schemes for various no...
متن کاملDistance Weighted Discrimination
High Dimension Low Sample Size statistical analysis is becoming increasingly important in a wide range of applied contexts. In such situations, it is seen that the popular Support Vector Machine suffers from “data piling” at the margin, which can diminish generalizability. This leads naturally to the development of Distance Weighted Discrimination, which is based on Second Order Cone Programmin...
متن کاملDistance Weighted Discrimination
High Dimension Low Sample Size statistical analysis is becoming increasingly important in a wide range of applied contexts. In such situations, it is seen that the appealing discrimination method called the Support Vector Machine can be improved. The revealing concept is data piling at the margin. This leads naturally to the development of Distance Weighted Discrimination, which also is bas...
متن کاملSparse Distance Weighted Discrimination
Distance weighted discrimination (DWD) was originally proposed to handle the data piling issue in the support vector machine. In this paper, we consider the sparse penalized DWD for high-dimensional classification. The state-of-the-art algorithm for solving the standard DWD is based on second-order cone programming, however such an algorithm does not work well for the sparse penalized DWD with ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the American Statistical Association
سال: 2010
ISSN: 0162-1459,1537-274X
DOI: 10.1198/jasa.2010.tm08487