Support vector ordinal regression (SVOR) is a popular method to tackle ordinal regression
problems. However, until now there were no effective algorithms proposed to address …

Abstract The ν-Support Vector Regression (ν-SVR) is an effective regression learning
algorithm, which has the advantage of using a parameter ν on controlling the number of …

In a lot of real-world data mining and machine learning applications, data are provided by
multiple providers and each maintains private records of different feature sets about …

Cost-sensitive learning can be found in many real-world applications and represents an
important learning paradigm in machine learning. The recently proposed cost-sensitive …

The ν-support vector machine (ν-SVM) for classification has the advantage of using a
parameter ν on controlling the number of support vectors and margin errors. Recently, an …

The ν-Support Vector Machine (ν-SVM) for classification proposed by Schölkopf et al. has
the advantage of using a parameter ν on controlling the number of support vectors and …

The v-support vector classification (v-SVC) proposed by Schölkopf has the advantage of
using a regularization parameter v for controlling the number of support vectors and margin …

When the training data required by the data-driven model is insufficient or difficult to cover
the sample space completely, incorporating the prior knowledge and prior knowledge …

Cost-sensitive learning is an important field in machine learning, which widely exists in real-
world applications, such as cancer diagnosis, credit application, etc. Cost-sensitive support …