Results 11 to 20 of about 10,458 (157)
Improved stacking ensemble learning based on feature selection to accurately predict warfarin dose. [PDF]
Front Cardiovasc Med, 2023 BackgroundWith the rapid development of artificial intelligence, prediction of warfarin dose via machine learning has received more and more attention.
Wang M, Qian Y, Yang Y, Chen H, Rao WF.
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Stacking Ensemble Learning Model for Intrusion Detection in Electrical Substation
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)Electrical substations are crucial infrastructure in power transmission and distribution but are increasingly vulnerable to cyber threats. However, existing intrusion detection systems (IDS) face challenges such as high false positive rates, limited adaptability to emerging attack patterns, and imbalanced detection across different intrusion types ...
Mohammad Mahruf Alam +3 more
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Code Smell Detection Driven by Hybrid Feature Selection and Ensemble Learning [PDF]
Jisuanji gongcheng, 2022 Code smell is a software feature that violates basic design principles or coding standards.When introduced into a source code, code smell increases the cost and difficulty of its maintenance.Machine learning can outperform other code smell detection ...
AI Chenghao, GAO Jianhua, HUANG Zijie
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Software Defect Prediction Using Stacking Generalization of Optimized Tree-Based Ensembles
Applied Sciences, 2022 Software defect prediction refers to the automatic identification of defective parts of software through machine learning techniques. Ensemble learning has exhibited excellent prediction outcomes in comparison with individual classifiers.
Amal Alazba, Hamoud Aljamaan
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Future Internet, 2022 Forecasting the risk factor of the financial frontier markets has always been a very challenging task. Unlike an emerging market, a frontier market has a missing parameter named “volatility”, which indicates the market’s risk and as a result of the ...
Mst. Shapna Akter +3 more
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Multi-layer stacking ensemble learners for low footprint network intrusion detection
Complex & Intelligent Systems, 2022 Machine learning has become the standard solution to problems in many areas, such as image recognition, natural language processing, and spam detection.
Saeed Shafieian, Mohammad Zulkernine
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IEEE Open Journal of Intelligent Transportation Systems, 2020 Machine learning algorithms aim to improve the power of predictors over conventional regression models. This study aims to tap the predictive potential of crash mechanism-related variables using ensemble machine learning models.
Ang Ji, David Levinson
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Stacking ensemble learning for optical music recognition
Bulletin of Electrical Engineering and Informatics, 2023 The development of music culture has resulted in a problem called optical music recognition (OMR). OMR is a task in computer vision that explores the algorithms and models to recognize musical notation. This study proposed the stacking ensemble learning model to complete the OMR task using the common western musical notation (CWMN) musical notation ...
Francisco Calvin Arnel Ferano +2 more
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A comprehensive evaluation of ensemble learning methods and decision trees for predicting trauma patient discharge status using real-world data [PDF]
Archives of Trauma Research, 2023 Background: Trauma registries collect and document data about the acute injury care in hospitals. The goal of trauma care systems is to reduce injury occurrence and enhance trauma patient survival rates.
Zahra Kohzadi +4 more
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Applied Water Science, 2022 The present research aims to build a unique ensemble model based on a high-resolution groundwater potentiality model (GPM) by merging the random forest (RF) meta classifier-based stacking ensemble machine learning method with high-resolution groundwater ...
Javed Mallick +2 more
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