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An Enhanced Ensemble Learning Method for Sentiment Analysis based on Q-learning
Ensemble learning is a powerful technique for combining multiple classifiers to achieve improved performance. However, the challenge of applying...
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Distributed Ensemble Method Using Deep Learning to Detect DDoS Attacks in IoT Networks
The widespread adoption of Internet of Things (IoT) devices has increased exponentially in recent years. Consequently, the security risks and...
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An Optimized Bagging Learning with Ensemble Feature Selection Method for URL Phishing Detection
This study proposes and implements an ensemble feature selection with a bagging classifier for URL phishing detection. Feature Selection is essential...
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Enhanced Bearing Fault Diagnosis Through Trees Ensemble Method and Feature Importance Analysis
PurposeThis research introduces a groundbreaking method for bearing defect detection. It leverages ensemble machine learning (ML) models and conducts...
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A Sarsa reinforcement learning hybrid ensemble method for robotic battery power forecasting
Building a rail transit workshop with efficient data interconnection has become an inevitable trend in the transformation and development of the...
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Milling surface roughness prediction method based on spatiotemporal ensemble learning
Surface roughness is widely used for product quality assessment due to its ability to accurately portray the fatigue strength, wear resistance,...
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Intelligent prediction method for fracture pressure based on stacking ensemble algorithm
Fracture pressure is an important reference for wellbore stability analysis and hydraulic fracturing. Considering the low prediction accuracy,...
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Stacked Ensemble Feature Selection Method for Kannada Documents Categorization
In document-level text mining, feature selection is crucial for lowering ambiguity which in turn enhances classifier performance. The selection of...
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A novel metamodel-based multi-objective optimization method using adaptive multi-regional ensemble of metamodels
The optimization of the engineering system is becoming more and more significant as time progresses, and a large number of metamodel-based...
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A federated learning algorithm using parallel-ensemble method on non-IID datasets
Traditional federated learning algorithms suffer from considerable performance reduction with non-identically and independently distributed datasets....
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Efficacy of Ensemble Learning Method over Individual Classifier for Rainfall Forecasting in Eastern India
Severe rainfall has seriously threatened human health and survival. Natural catastrophes such as floods, droughts, and many other natural disasters...
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Development of Heavy Rain Damage Prediction Technique Based on Optimization and Ensemble Method
Korea’s early warning system for flood disaster management is starting preparations for flood response by the heavy rain advisory (HRA) of the Korea...
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Robust Drug Use Detection on X: Ensemble Method with a Transformer Approach
There is a growing trend for groups associated with drug use to exploit social media platforms to propagate content that poses a risk to the...
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Deep Learning Based COVID-19 Detection via Hard Voting Ensemble Method
Healthcare systems throughout the world are under a great deal of strain because to the continuing COVID-19 epidemic, making early and precise...
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Adversarial defense method based on ensemble learning for modulation signal intelligent recognition
Modulation signal intelligent recognition model based on deep learning is widely used in the field of radio signal intelligent processing, but the...
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A real-valued label noise cleaning method based on ensemble iterative filtering with noise score
Real-world data always contain noise for a variety of reasons. In a regression task, noisy labels interfere with the construction of an accurate...
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Ensemble classification based optimized transfer learning feature method for early stage diagnosis of diabetic retinopathy
Early diagnosis of the diabetic retinopathy is important in preventing vision loss. The intense workload of the experts and the long time analysis of...
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Fault Identification Method for In-Core Self-Powered Neutron Detectors Combing Graph Convolutional Network and Stacking Ensemble Learning
Self-powered neutron detectors (SPNDs) play a critical role in monitoring the safety margins and overall health of reactors, directly affecting safe...
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Early Malignant Mesothelioma Detection Using Ensemble of Naive Bayes Under Decorate Ensemble Framework
The growing role of machine learning in early malignant mesothelioma highlights the significance of this study. This study analyzes and suggests an...
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A multiple criteria ensemble pruning method for binary classification based on D-S theory of evidence
Ensemble pruning becomes an important stage in multiple classifier systems, and it has been widely applied to solve binary classification problems....
