A new machine learning technique for an accurate diagnosis of coronary artery disease
Background and objective Coronary artery disease (CAD) is one of the commonest diseases
around the world. An early and accurate diagnosis of CAD allows a timely administration of …
around the world. An early and accurate diagnosis of CAD allows a timely administration of …
Joint metric learning-based class-specific representation for image set classification
With the rapid advances in digital imaging and communication technologies, recently image
set classification has attracted significant attention and has been widely used in many real …
set classification has attracted significant attention and has been widely used in many real …
Intuitionistic fuzzy twin support vector machines
Fuzzy twin support vector machine (FTSVM) is an effective machine learning technique that
is able to overcome the negative impact of noise and outliers in tackling data classification …
is able to overcome the negative impact of noise and outliers in tackling data classification …
Machine learning-based fault location for smart distribution networks equipped with micro-PMU
Faults in distribution networks occur unpredictably, causing a threat to public safety and
resulting in power outages. Automated, efficient, and precise detection of faulty sections …
resulting in power outages. Automated, efficient, and precise detection of faulty sections …
Machine learning prediction of nanoparticle in vitro toxicity: A comparative study of classifiers and ensemble-classifiers using the Copeland Index
Abstract Nano-Particles (NPs) are well established as important components across a broad
range of products from cosmetics to electronics. Their utilization is increasing with their …
range of products from cosmetics to electronics. Their utilization is increasing with their …
Coupling privileged kernel method for multi-view learning
Multi-view learning concentrates on fully using the data collected from diverse domains or
obtained from various feature extractors to learn effectively. The consensus and …
obtained from various feature extractors to learn effectively. The consensus and …
Coal classification method based on visible-infrared spectroscopy and an improved multilayer extreme learning machine
Y Mao, BT Le, D Xiao, D He, C Liu, L Jiang, Z Yu… - Optics & Laser …, 2019 - Elsevier
Coal classification is an indispensable task in coal mining and production. The traditional
method of coal classification has the disadvantages of high cost, low speed and low …
method of coal classification has the disadvantages of high cost, low speed and low …
Least squares projection twin support vector clustering (LSPTSVC)
B Richhariya, M Tanveer… - Information …, 2020 - Elsevier
Clustering is a prominent unsupervised learning technique. In the literature, many plane
based clustering algorithms are proposed, such as the twin support vector clustering …
based clustering algorithms are proposed, such as the twin support vector clustering …
Two-directional two-dimensional kernel canonical correlation analysis
Two-directional two-dimensional canonical correlation analysis ((2D) CCA) directly seeks
linear relationship between different image data sets without reshaping images into vectors …
linear relationship between different image data sets without reshaping images into vectors …
Kernel learning and optimization with Hilbert–Schmidt independence criterion
T Wang, W Li - International Journal of Machine Learning and …, 2018 - Springer
Measures of statistical dependence between random variables have been successfully
applied in many machine learning tasks, such as independent component analysis, feature …
applied in many machine learning tasks, such as independent component analysis, feature …