Results 51 to 60 of about 6,303,129 (314)
Predicting seismic-induced liquefaction through ensemble learning frameworks
Scientific Reports, 2019 The regional nature of liquefaction records and limited information available for a certain set of explanatories motivate the development of complex prediction techniques.
Mohammad H. Alobaidi +2 more
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A Comparative Analysis of Ensemble Classifiers: Case Studies in Genomics
, 2013 The combination of multiple classifiers using ensemble methods is increasingly important for making progress in a variety of difficult prediction problems. We present a comparative analysis of several ensemble methods through two case studies in genomics,
Pandey, Gaurav, Whalen, Sean
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An approach for multiclass skin lesion classification based on ensemble learning
Informatics in Medicine Unlocked, 2021 Background and objective: Skin cancer is recognized as the most common kind of cancer in the world. It could be deadly if not identified at the primary stage, which makes early detection very crucial. It is possible to identify it with the naked eye, but
Zillur Rahman +4 more
semanticscholar +1 more source
Optimized Ensemble Learning Approach with Explainable AI for Improved Heart Disease Prediction
Inf.Recent advances in machine learning (ML) have shown great promise in detecting heart disease. However, to ensure the clinical adoption of ML models, they must not only be generalizable and robust but also transparent and explainable.
Ibomoiye Domor Mienye, N. Jere
semanticscholar +1 more source
BMC Bioinformatics, 2021 Background Atrial fibrillation is a paroxysmal heart disease without any obvious symptoms for most people during the onset. The electrocardiogram (ECG) at the time other than the onset of this disease is not significantly different from that of normal ...
Cai Wu +8 more
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Ensemble learning of linear perceptron; Online learning theory
, 2004 Within the framework of on-line learning, we study the generalization error of an ensemble learning machine learning from a linear teacher perceptron.
Breiman L. +8 more
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Journal of Science and Arts, 2022 Artificial intelligence is a method that is increasingly becoming widespread in all areas of life and enables machines to imitate human behavior. Machine learning is a subset of artificial intelligence techniques that use statistical methods to enable machines to evolve with experience.
SELIN CEREN TURAN, MEHMET ALI CENGIZ
openaire +1 more source
Flood Susceptibility Assessment with Random Sampling Strategy in Ensemble Learning (RF and XGBoost)
Remote SensingDue to the complex interaction of urban and mountainous floods, assessing flood susceptibility in mountainous urban areas presents a challenging task in environmental research and risk analysis.
Hancheng Ren +6 more
semanticscholar +1 more source
Cross corpus multi-lingual speech emotion recognition using ensemble learning
Complex & Intelligent Systems, 2021 Receiving an accurate emotional response from robots has been a challenging task for researchers for the past few years. With the advancements in technology, robots like service robots interact with users of different cultural and lingual backgrounds ...
Wisha Zehra +4 more
semanticscholar +1 more source
Ensemble Techniques Based Risk Classification for Maternal Health During Pregnancy
Ilkom Jurnal IlmiahThis research focuses on the critical aspect of maternal health during pregnancy, emphasizing the need for early detection and intervention to address potential risks to both mothers and infants. Leveraging various classification methods, including Naïve
Nurul Fathanah Mustamin +3 more
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