Neighborhood rough sets based attribute reduction, as a common dimension reduction
method, has been widely used in machine learning and data mining. Each attribute has the …

Egocentric 3D human pose estimation using a single fisheye camera has become popular
recently as it allows capturing a wide range of daily activities in unconstrained environments …

In three-way decision, how to reflect the risk attitude in determining decision rules is an
important issue. In the classical three-way decision model, loss functions are used to …

In the field of rough set, how to improve the efficiency of obtaining reduct has been paid
much attention to. One of the typical strategies is to reduce the number of comparisons …

Neighborhood rough set is a useful mathematic tool to describe uncertainty in mixed data.
Feature selection based on neighborhood rough set has been studied widely. However …

As a fundamental granular computing strategy, neighborhood granulation has been
acknowledged as an intuitive and effective approach to feature evaluation and selection …

Abstract Information gain, as an important feature measure, plays a vital role in the process
of feature selection. Most of existing information gain-based feature selection algorithms are …

Neighborhood Learning (NL) is a paradigm covering theories and techniques of
neighborhood, which facilitates data organization, representation and generalization. While …

In this study, a granular ball based selector was developed for reducing the dimensions of
data from the perspective of attribute reduction. The granular ball theory offers a data …

In neighborhood rough set, radius is a key factor. Different radii may generate different
neighborhood relations for discriminating samples. Unfortunately, it is possible that two …