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Regression Analysis

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Image Quality Assessment Using Human Visual DOG Model Fused With Random Forest.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Objective image quality assessment (IQA) plays an important role in the development of multimedia applications. Prediction of IQA metric should be consistent with human perception. The release of the newest IQA database (TID2013) challenges most of t...

Deep sparse multi-task learning for feature selection in Alzheimer's disease diagnosis.

Brain structure & function
Recently, neuroimaging-based Alzheimer's disease (AD) or mild cognitive impairment (MCI) diagnosis has attracted researchers in the field, due to the increasing prevalence of the diseases. Unfortunately, the unfavorable high-dimensional nature of neu...

Accuracy of latent-variable estimation in Bayesian semi-supervised learning.

Neural networks : the official journal of the International Neural Network Society
Hierarchical probabilistic models, such as Gaussian mixture models, are widely used for unsupervised learning tasks. These models consist of observable and latent variables, which represent the observable data and the underlying data-generation proce...

Asymptotic accuracy of Bayesian estimation for a single latent variable.

Neural networks : the official journal of the International Neural Network Society
In data science and machine learning, hierarchical parametric models, such as mixture models, are often used. They contain two kinds of variables: observable variables, which represent the parts of the data that can be directly measured, and latent v...

Applying a novel combination of techniques to develop a predictive model for diabetes complications.

PloS one
Among the many related issues of diabetes management, its complications constitute the main part of the heavy burden of this disease. The aim of this paper is to develop a risk advisor model to predict the chances of diabetes complications according ...

Noninvasive reconstruction of cardiac transmembrane potentials using a kernelized extreme learning method.

Physics in medicine and biology
Non-invasively reconstructing the cardiac transmembrane potentials (TMPs) from body surface potentials can act as a regression problem. The support vector regression (SVR) method is often used to solve the regression problem, however the computationa...

A pressure control method for emulsion pump station based on Elman neural network.

Computational intelligence and neuroscience
In order to realize pressure control of emulsion pump station which is key equipment of coal mine in the safety production, the control requirements were analyzed and a pressure control method based on Elman neural network was proposed. The key techn...

Designing of an artificial neural network model to evaluate the association of three combined Y-specific microsatellite loci on the actual and predicted postthaw motility in crossbred bull semen.

Theriogenology
The freezing of bull semen significantly hamper the motility of sperm which reduces the conception rate in dairy cattle. The prediction of postthaw motility (PTM) before freezing will be useful to take the decision on discarding or freezing of the ge...

Online monitoring and control of particle size in the grinding process using least square support vector regression and resilient back propagation neural network.

ISA transactions
Particle size soft sensing in cement mills will be largely helpful in maintaining desired cement fineness or Blaine. Despite the growing use of vertical roller mills (VRM) for clinker grinding, very few research work is available on VRM modeling. Thi...