Majoration-Minimization for Sparse SVMs
Several decades ago, Support Vector Machines (SVMs) were introduced for performing binary classification tasks, under a supervised framework. Nowadays, they often outperform other supervised methods and remain one of the most popular approaches in the machine learning arena.
Benfenati, Alessandro +7 more
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Cardiorespiratory Markers of Type 2 Diabetes: Machine Learning-Based Analysis. [PDF]
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Random subspace-based ensemble classifier for high-dimensional data Using SPARK. [PDF]
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AI-Driven prediction of body weight in chicken genotypes with different growth rates. [PDF]
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Hybrid EfficientNet B4 and SVM framework for rapid and accurate bone cancer diagnosis from X-rays. [PDF]
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GC-IMS-based analysis of serum volatile organic compounds for diagnosis of gastric cancer. [PDF]
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The Evaluation of Machine Learning Models Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF-MS) Spectra for the Prediction of Antibiotic Resistance in Klebsiella pneumoniae. [PDF]
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Spectral analysis of ECG and SpO₂ for machine learning classification of Sleep-Disordered breathing. [PDF]
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Climate and biocrust types jointly regulate soil multifunctionality and quality in drylands: evidence from the Gurbantunggut Desert. [PDF]
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