Quality over quantity: Sampling high probability rare events with the weighted ensemble algorithm
Sign Up to like & getrecommendations! Published in 2022 at "Journal of computational chemistry"
DOI: 10.1002/jcc.27054
Abstract: The prediction of (un)binding rates and free energies is of great significance to the drug design process. Although many enhanced sampling algorithms and approaches have been developed, there is not yet a reliable workflow to… read more here.
Keywords: weighted ensemble; high probability; quantity sampling; free energies ... See more keywords
Wepy: A Flexible Software Framework for Simulating Rare Events with Weighted Ensemble Resampling
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DOI: 10.1021/acsomega.0c03892
Abstract: Here, we introduce the open-source software framework wepy (https://github.com/ADicksonLab/wepy) which is a toolkit for running and analyzing weighted ensemble (WE) simulations. The wepy toolkit is in pure Python and as such is highly portable and… read more here.
Keywords: wepy; software framework; simulating rare; weighted ensemble ... See more keywords
Double weighted ensemble clustering for cancer subtypes analysis
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DOI: 10.1109/access.2022.3167031
Abstract: The era of big data provides the possibility of precision medicine. The most important idea we have for cancer is to divide and treat. Theoretically, each person’s cancer should be different, so it is very… read more here.
Keywords: weighted ensemble; cancer; double weighted; analysis ... See more keywords
DME: An Adaptive and Just-in-Time Weighted Ensemble Learning Method for Classifying Block-Based Concept Drift Steam
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DOI: 10.1109/access.2022.3222178
Abstract: This study proposes a novel incremental learning algorithm called distribution matching ensemble (DME) in context of adaptive weighted ensemble learning. In particular, DME estimates the distribution of each received data block by Gaussian mixture model… read more here.
Keywords: weighted ensemble; data block; ensemble learning; dme ... See more keywords
Locally Weighted Ensemble-Detection-Based Adaptive Random Forest Classifier for Sensor-Based Online Activity Recognition for Multiple Residents
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DOI: 10.1109/jiot.2021.3139330
Abstract: In recent years, various approaches for multiresident human activity recognition (HAR) in a smart indoor environment have been developed and improved along with the rapid development of sensors and AI technologies. Research in data stream-based… read more here.
Keywords: weighted ensemble; ensemble detection; detection based; activity recognition ... See more keywords
A Weighted Ensemble Learning Algorithm Based on Diversity Using a Novel Particle Swarm Optimization Approach
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DOI: 10.3390/a13100255
Abstract: In ensemble learning, accuracy and diversity are the main factors affecting its performance. In previous studies, diversity was regarded only as a regularization term, which does not sufficiently indicate that diversity should implicitly be treated… read more here.
Keywords: diversity; weighted ensemble; accuracy; particle swarm ... See more keywords
Divergence-Based Locally Weighted Ensemble Clustering with Dictionary Learning and L2,1-Norm
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DOI: 10.3390/e24101324
Abstract: Accurate clustering is a challenging task with unlabeled data. Ensemble clustering aims to combine sets of base clusterings to obtain a better and more stable clustering and has shown its ability to improve clustering accuracy.… read more here.
Keywords: weighted ensemble; divergence based; based locally; ensemble clustering ... See more keywords
Predictive Churn Modeling for Sustainable Business in the Telecommunication Industry: Optimized Weighted Ensemble Machine Learning
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DOI: 10.3390/su15118631
Abstract: Customers are prominent resources in every business for its sustainability. Therefore, predicting customer churn is significant for reducing churn, particularly in the high-churn-rate telecommunications business. To identify customers at risk of churning, tactical marketing actions… read more here.
Keywords: weighted ensemble; business; machine learning; optimized weighted ... See more keywords