Insect pest management is one of the main ways to improve the crop yield and quality in
agriculture and it can accurately and timely detect insect pests, which is of great significance …

The three-way classifications aim to divide the universe of objects into three disjoint regions,
ie, acceptance, rejection, and non-commitment regions. We can induce different types of …

In extracting hidden information from a data, its high dimension can create challenges in the
quality of the extracted information and the search space size. Attribute reduction based on …

Abstract Machine learning algorithms treat credit risk prediction as a binary classification
problem. However, two-way decisions with a single threshold force to make either a default …

Decision-theoretic rough sets (DTRSs), which can be considered as generalized rough set
models produced by Bayesian risk minimum and three-way decisions (3WD) theories, have …

Crime linkage is a difficult task and is of great significance to maintaining social security. It
can be treated as a binary classification problem. Some crimes are difficult to determine …

Decision-theoretic rough set (DTRS) and multi-granulation rough set (MGRS) are two
important extended types of Pawlak's classical rough set model. The two generalized rough …

The paper proposes a taxonomy for categorizing the main features of the supervised
learning classification problems and a notation for the identification of the supervised …

The ORESTE (organísation, rangement et Synthèse de données relarionnelles, in French,
meaning organization, storage and synthesis of relevant data in English) method is an …

Purpose This paper aims to utilize machine learning and soft computing to propose a new
method of rough sets using deep learning architecture for many real-world applications …