This study evaluates the predictive performance of traditional and machine learning-based models in forecasting NFL team winning percentages over a 21-season dataset (2003–2023). Specifically, we ...
Abstract: In recent years, High Entropy Alloys (HEAs) have gained significant interest due to their unique properties such as high strength, wear resistance, and high temperature stability. However, ...
ABSTRACT: Introduction: Breast Cancer (BC) remains a significant health concern worldwide, and accurate prediction of its recurrence after surgery is vital for patient management and treatment ...
tweet_classification/ │ ├── data/ # CSV dataset files │ └── labeled_data.csv │ ├── models/ # Contains each model's training function │ ├── knn_model.py │ ├── svm_model.py │ ├── ...
High-entropy alloy materials demonstrate exceptional catalytic properties due to their distinctive multi-component attributes and electronic effects. Nonetheless, the extensive data landscape of ...
ABSTRACT: This study evaluates the performance and reliability of a vision transformer (ViT) compared to convolutional neural networks (CNNs) using the ResNet50 model in classifying lung cancer from ...
Sample selection improves the efficiency and effectiveness of machine learning models by providing informative and representative samples. Typically, samples can be modeled as a sample graph, where ...
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