Feature selection plays a critical role in biomedical data mining, driven by increasing feature
dimensionality in target problems and growing interest in advanced but computationally …

Abstract Intelligent Fault-Tolerant Control (IFTC) refers to the applications of machine
learning algorithms for fault diagnosis and design of Fault-Tolerant Control (FTC). The …

Contactless fault diagnosis is one of the most important technique for fault identification of
equipment. Based on the idea of contactless fault diagnosis, this paper presents a sound …

In order to improve the classification accuracy, a preprocessing step is used to pre-filter
some redundant or irrelevant features before decision tree construction. And a new feature …

Nowadays, with emerge the multi-label datasets, the multi-label learning processes attracted
interest and increasingly applied to different fields. In such learning processes, unlike single …

With the rapid advancement of big data technology, high-dimensional datasets comprising
multi-label data have become prevalent in various fields. However, these datasets often …

In this paper, for the first time, a feature selection procedure is modeled as a multi-criteria
decision making (MCDM) process. This method is applied to a multi-label data and we have …

In recent years, multi-label learning becomes a trending topic in machine learning and data
mining. This type of learning deals with data that each instance is associated with more than …

For the first time, the ensemble feature selection is modeled as a Multi-Criteria Decision-
Making (MCDM) process in this paper. For this purpose, we used the VIKOR method as a …

Curse of dimensionality is known as big challenges in data mining, pattern recognition,
computer vison and machine learning in recent years. Feature selection and feature …