Monitoring methods of human body joints: State-of-the-art and research challenges
The world's population is aging: the expansion of the older adult population with multiple
physical and health issues is now a huge socio-economic concern worldwide. Among these …
physical and health issues is now a huge socio-economic concern worldwide. Among these …
Infinite latent feature selection: A probabilistic latent graph-based ranking approach
Feature selection is playing an increasingly significant role with respect to many computer
vision applications spanning from object recognition to visual object tracking. However, most …
vision applications spanning from object recognition to visual object tracking. However, most …
Infinite feature selection: a graph-based feature filtering approach
We propose a filtering feature selection framework that considers subsets of features as
paths in a graph, where a node is a feature and an edge indicates pairwise (customizable) …
paths in a graph, where a node is a feature and an edge indicates pairwise (customizable) …
Experimental analysis of machine learning methods for credit score classification
Credit scoring concerns with emerging empirical model to assist the financial institutions for
financial decision-making process. Credit risk analysis plays a vital role for decision-making …
financial decision-making process. Credit risk analysis plays a vital role for decision-making …
Classification of depression patients and normal subjects based on electroencephalogram (EEG) signal using alpha power and theta asymmetry
Abstract Depression or Major Depressive Disorder (MDD) is a mental illness which
negatively affects how a person thinks, acts or feels. MDD has become a major disease …
negatively affects how a person thinks, acts or feels. MDD has become a major disease …
Feature selection library (MATLAB toolbox)
G Roffo - arxiv preprint arxiv:1607.01327, 2016 - arxiv.org
Feature Selection Library (FSLib) is a widely applicable MATLAB library for Feature
Selection (FS). FS is an essential component of machine learning and data mining which …
Selection (FS). FS is an essential component of machine learning and data mining which …
[HTML][HTML] Prediction of paroxysmal atrial fibrillation using new heart rate variability features
Paroxysmal atrial fibrillation (PAF) is a cardiac arrhythmia that can eventually lead to heart
failure or stroke if left untreated. Early detection of PAF is therefore crucial to prevent any …
failure or stroke if left untreated. Early detection of PAF is therefore crucial to prevent any …
GBRS: A Unified Granular-Ball Learning Model of Pawlak Rough Set and Neighborhood Rough Set
Pawlak rough set (PRS) and neighborhood rough set (NRS) are the two most common
rough set theoretical models. Although the PRS can use equivalence classes to represent …
rough set theoretical models. Although the PRS can use equivalence classes to represent …
Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity
Although many deep learning models-based medical applications are performance-driven,
ie, accuracy-oriented, their explainability is more critical. This is especially the case with …
ie, accuracy-oriented, their explainability is more critical. This is especially the case with …
An efficient and accurate rough set for feature selection, classification, and knowledge representation
This paper presents a strong data-mining method based on a rough set, which can
simultaneously realize feature selection, classification, and knowledge representation …
simultaneously realize feature selection, classification, and knowledge representation …