Topics

Ensemble of extreme learning machines for multivariate calibration of near-infrared spectroscopy.

07:00 EST 24th December 2019 | BioPortfolio

Summary of "Ensemble of extreme learning machines for multivariate calibration of near-infrared spectroscopy."

Inspired by the attractive features of extreme learning machine (ELM), a simple ensemble ELM algorithm, named EELM, is proposed for multivariate calibration of near-infrared spectroscopy. Such an algorithm takes full advantage of random initialization of the weights of the hidden layer in ELM for obtaining the diversity between member models. Also, by combining a large number of member models, the stability of the final prediction can be greatly improved and the ensemble model outperforms its best member model. Compared with partial least-squares (PLS), the superiority of EELM is attributed to its inherent characteristics of high learning speed, simple structure and excellent predictive performance. Three NIR spectral datasets concerning solid samples are used to verify the proposed algorithm in terms of both the accuracy and robustness. The results confirmed the superiority of EELM to classic PLS. Also, even if the experiment is done on NIR datasets, it provides a good reference for other spectral calibration.

Affiliation

Journal Details

This article was published in the following journal.

Name: Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
ISSN: 1873-3557
Pages: 117982

Links

DeepDyve research library

PubMed Articles [8629 Associated PubMed Articles listed on BioPortfolio]

Sparse Ensemble Machine Learning to Improve Robustness of Long-term Decoding in iBMIs.

This paper presents a novel sparse ensemble based machine learning approach to enhance robustness of intracortical Brain Machine Interfaces (iBMIs) in the face of non-stationary distribution of input ...

SVR ensemble based continuous blood pressure prediction using multi-channel photoplethysmogram.

In this paper, a continuous non-occluding blood pressure (BP) prediction method is proposed using multiple photoplethysmogram (PPG) signals. In the new method, BP is predicted by a committee machine o...

Ensemble-based kernel learning for a class of data assimilation problems with imperfect forward simulators.

Simulator imperfection, often known as model error, is ubiquitous in practical data assimilation problems. Despite the enormous efforts dedicated to addressing this problem, properly handling simulato...

Online sequential class-specific extreme learning machine for binary imbalanced learning.

Many real-world applications suffer from the class imbalance problem, in which some classes have significantly fewer examples compared to the other classes. In this paper, we focus on online sequentia...

Identifying cancer targets based on machine learning methods via Chou's 5-steps rule and general pseudo components.

In recent years, the successful implementation of human genome project has made people realize that genetic, environmental and lifestyle factors should be combined together to study cancer due to the ...

Clinical Trials [2379 Associated Clinical Trials listed on BioPortfolio]

Ensemble Programme an Early Intervention for Informal Caregivers of Psychiatric Patients

This study focuses on the difficulties of maintaining optimal psychological health and quality of life for caregivers in adult psychiatry while they play an important role in helping patie...

Endoscopic vs. Suction Device Calibration in Sleeve Gastrectomy

This study aims to compare the difference in staple usage and post-operative GERD (heartburn) between patients that had an endoscope used versus patients that had a suction calibration sys...

NightOwl SpO2 Calibration Study

Calibration of a software module that computes Oxygen saturation(SpO2) based on photoplethysmography (PPG) traces acquired by the NightOwl reflectance-based PPG sensor which is placed on t...

Evaluation of ExSpiron™ Measurements Derived Without Patient Specific Calibration

Previous studies have shown that the ExSpiron™ can provide non-invasive, real-time, accurate measurements of minute ventilation (MV), tidal volume (TV) and respiratory rate (RR) after ca...

Extreme Lipids Repository

This is a prospective, observational study to establish a repository of samples from patients with extreme lipid phenotypes including but not limited to hyperlipidemia, dyslipidemia, hyper...

Medical and Biotech [MESH] Definitions

A set of techniques used when variation in several variables has to be studied simultaneously. In statistics, multivariate analysis is interpreted as any analytic method that allows simultaneous study of two or more dependent variables.

Process in which individuals take the initiative, in diagnosing their learning needs, formulating learning goals, identifying resources for learning, choosing and implementing learning strategies and evaluating learning outcomes (Knowles, 1975)

That branch of learning which brings together theories and studies on communication and control in living organisms and machines.

Measurement of the regional temperature of the body or an organ by infrared sensing devices, based on self-emanating infrared radiation.

That portion of the electromagnetic spectrum usually sensed as heat. Infrared wavelengths are longer than those of visible light, extending into the microwave frequencies. They are used therapeutically as heat, and also to warm food in restaurants.

Quick Search


DeepDyve research library

Searches Linking to this Article