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Published in 2023 at "Statistics in Medicine"
DOI: 10.1002/sim.9655
Abstract: In this work we introduce the personalized online super learner (POSL), an online personalizable ensemble machine learning algorithm for streaming data. POSL optimizes predictions with respect to baseline covariates, so personalization can vary from completely…
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Keywords:
time;
posl;
time series;
personalized online ... See more keywords
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Published in 2021 at "Journal of The Institution of Engineers (India): Series B"
DOI: 10.1007/s40031-021-00599-1
Abstract: Analyzing dissolved gases in the transformer's mineral oil helps to detect and classify the systemic faults in electric power transformers. Formerly, empirical methods such as Rogers ratio, Duval triangles 1–4–5, and pentagons 1–2 were used…
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Keywords:
ensemble machine;
transformer;
learning methods;
power transformers ... See more keywords
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Published in 2020 at "Electric Power Systems Research"
DOI: 10.1016/j.epsr.2020.106904
Abstract: Abstract Advanced metering infrastructure allows the two-way sharing of information between smart meters and utilities. However, it makes smart grids more vulnerable to cyber-security threats such as energy theft. This study suggests ensemble machine learning…
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Keywords:
machine learning;
learning models;
energy;
energy theft ... See more keywords
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Published in 2018 at "Journal of anxiety disorders"
DOI: 10.1016/j.janxdis.2018.10.004
Abstract: Posttraumatic stress disorder (PTSD) develops in a substantial minority of emergency room admits. Inexpensive and accurate person-level assessment of PTSD risk after trauma exposure is a critical precursor to large-scale deployment of early interventions that…
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Keywords:
machine;
machine learning;
ensemble machine;
screening status ... See more keywords
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Published in 2022 at "Environmental science & technology"
DOI: 10.1021/acs.est.1c04076
Abstract: 3D-grid-based chemical transport models, such as the Community Multiscale Air Quality (CMAQ) modeling system, have been widely used for predicting concentrations of ambient air pollutants. However, typical horizontal resolutions of nationwide CMAQ simulations (12 ×…
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Keywords:
framework;
ensemble machine;
bayesian ensemble;
machine learning ... See more keywords
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Published in 2021 at "International Journal of Digital Earth"
DOI: 10.1080/17538947.2020.1860145
Abstract: ABSTRACT In this paper, we developed highly accurate ensemble machine learning models integrating Reduced Error Pruning Tree (REPT) as a base classifier with the Bagging (B), Decorate (D), and Random Subspace (RSS) ensemble learning techniques…
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Keywords:
machine learning;
learning models;
error;
ensemble machine ... See more keywords
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1
Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3224781
Abstract: Phishing is a kind of worldwide spread cybercrime that uses disguised websites to trick users into downloading malware or providing personally sensitive information to attackers. With the rapid development of artificial intelligence, more and more…
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Keywords:
sufficiency ensemble;
machine;
machine learning;
phishing websites ... See more keywords
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Published in 2020 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2019.2962708
Abstract: 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 neural data across time. Each classifier in…
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Keywords:
sparse ensemble;
ensemble machine;
learning improve;
term ... See more keywords
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Published in 2022 at "Journal of Healthcare Engineering"
DOI: 10.1155/2022/6963891
Abstract: The endeavor to detect human activities and behaviors is targeted as a real-time detection mechanism that tends to predict the form of human motions and actions. Though sensors like accelerometer and gyroscopes are noticeable in…
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Keywords:
machine;
employment ensemble;
machine learning;
ensemble machine ... See more keywords
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Published in 2019 at "BMC Genomics"
DOI: 10.1186/s12864-019-6380-z
Abstract: BackgroundAssembly and function of neuronal synapses require the coordinated expression of a yet undetermined set of genes. Previously, we had trained an ensemble machine learning model to assign a probability of having synaptic function to…
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Keywords:
machine learning;
catalogue putative;
ensemble machine;
synaptic genes ... See more keywords
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Published in 2022 at "Environmental Health Perspectives"
DOI: 10.1289/ehp11438
Abstract: We appreciate the comments by Stafoggia et al. on our article. We would like to clarify that our article aimed to introduce a novel methodology, deep ensemble machine learning (DEML), to estimate concentrations of air…
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Keywords:
deep ensemble;
machine;
machine learning;
monitoring ... See more keywords