With the potentially massive, foundational shift of ChromeOS to the Android kernel on the horizon, there’s been a ton of speculation about what the future of our favorite operating system will ...
Precision crack analysis in concrete structures using CNN, SVM, and KNN: a machine learning approach
Cracks in structures are discontinuities that occur due to stress, material degradation, or design flaws, compromising structural integrity. Detecting and analyzing cracks is crucial for assessing ...
Introduction: Image and near-infrared (NIR) spectroscopic data are widely used for constructing analytical models in precision agriculture. While model interpretation can provide valuable insights for ...
🧠 Support Vector Machines (SVM) for Breast Cancer Classification 📌 Objective Use Support Vector Machines (SVMs) for binary classification of breast cancer (Malignant vs. Benign). The project ...
Abstract: Support Vector Machine (SVM) is a widely used algorithm for classification, valued for its flexibility with kernels that effectively handle non-linear problems and high-dimensional data.
I propose adding a Multiple Kernel Learning (MKL) module for kernel optimization in kernel-based methods (such as SVM) to scikit-learn. MKL is a more advanced approach compared to GridSearchCV, ...
Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...
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