Results 1 to 10 of about 65,886 (196)
PhishNet 1.0: optuna-optimized stacking ensemble with Boruta-based feature selection for phishing URL detection [PDF]
Scientific ReportsThe objective of this research is to enhance phishing detection through ensemble learning integrated with well-structured metaheuristic algorithms. Various classifiers, including Logistic Regression, Nearest Neighbors, Support Vector Machine, Decision ...
Achin Jain +7 more
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An interpretability heart disease prediction model based on stacking ensemble with SHAP [PDF]
Frontiers in Molecular BiosciencesIntroductionIn the big data era, healthcare data has grown exponentially, presenting opportunities to explore the pathogenesis of heart disease. Clarifying the correlations between health indicators and heart disease is crucial for early prevention. This
Yanjie Chen +5 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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Journal of Rock Mechanics and Geotechnical Engineering, 2021 Slope failures lead to catastrophic consequences in numerous countries and thus the stability assessment for slopes is of high interest in geotechnical and geological engineering researches.
Navid Kardani +3 more
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Prediction of Parkinson’s Disease Depression Using LIME-Based Stacking Ensemble Model
Mathematics, 2023 Depression symptoms are comparable to Parkinson’s disease symptoms, including attention deficit, fatigue, and sleep disruption, as well as symptoms of dementia such as apathy.
Hung Viet Nguyen, Haewon Byeon
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A stacking ensemble learning framework for genomic prediction [PDF]
Frontiers in Genetics, 2020 Abstract Background: Machine learning (ML) is perhaps the most useful for the interpretation of large genomic datasets. However, the performance of a single machine learning method in genomic selection (GS) was unsatisfactory in existing research.
Mang Liang +11 more
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LIME-based ensemble machine for predicting performance status of patients with liver cancer
Digital Health, 2023 Objective The Eastern Cooperative Oncology Group performance status (ECOG PS) is a widely recognized measure used to assess the functional abilities of cancer patients and predict their prognosis.
Hung Viet Nguyen, Haewon Byeon
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Applied Sciences, 2022 The accurate cost estimation of a construction project in the early stage plays a very important role in successfully completing the project. In the initial stage of construction, when the information necessary to predict construction cost is ...
Uyeol Park +3 more
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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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Stacked Ensemble Machine Learning for Range-Separation Parameters [PDF]
The Journal of Physical Chemistry Letters, 2021 High-throughput virtual materials and drug discovery based on density functional theory has achieved tremendous success in recent decades, but its power on organic semiconducting molecules suffered catastrophically from the self-interaction error until the optimally tuned range-separated hybrid (OT-RSH) exchange-correlation functionals were developed ...
Cheng-Wei Ju +4 more
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