On Regularization Based Twin Support Vector Regression with Huber Loss
نویسندگان
چکیده
منابع مشابه
Reduced twin support vector regression
Wepropose the reduced twin support vector regressor (RTSVR) that uses the notion of rectangular kernels to obtain significant improvements in execution time over the twin support vector regressor (TSVR), thus facilitating its application to larger sized datasets. & 2011 Elsevier B.V. All rights reserved.
متن کاملActive Regression with Adaptive Huber Loss
This paper addresses the scalar regression problem presenting a solution for optimizing the Huber loss in a general semi-supervised setting, which combines multi-view learning and manifold regularization. To this aim, we propose a principled algorithm to 1) avoid computationally expensive iterative solutions while 2) adapting the Huber loss threshold in a data-driven fashion and 3) actively bal...
متن کاملA weighted twin support vector regression
Twin support vector regression (TSVR) is a new regression algorithm, which aims at finding -insensitive upand down-bound functions for the training points. In order to do so, one needs to resolve a pair of smaller-sized quadratic programming problems (QPPs) rather than a single large one in a classical SVR. However, the same penalties are given to the samples in TSVR. In fact, samples in the di...
متن کاملA novel twin support vector regression
Twin support vector regression (TSVR), as an effective regression machine, solves a pair of smaller-sized quadratic programming problems (QPPs) rather than a single large one as in the classical support vector regression (SVR), which makes the learning speed of TSVR approximately 4 times faster than that of the SVR. However, the empirical risk minimization principle is implemented in TSVR, whic...
متن کاملOn implicit Lagrangian twin support vector regression by Newton method
In this work, an implicit Lagrangian for the dual twin support vector regression is proposed. Our formulation leads to determining non-parallel ε –insensitive downand upbound functions for the unknown regressor by constructing two unconstrained quadratic programming problems of smaller size, instead of a single large one as in the standard support vector regression (SVR). The two related suppor...
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: Neural Processing Letters
سال: 2021
ISSN: 1370-4621,1573-773X
DOI: 10.1007/s11063-020-10380-y