A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral analysis and SVM classification, the approach improves ...

Moving cannabis to a category of drugs that includes some common medicines will have implications for research, businesses and patients. By Jan Hoffman President Trump on Thursday ordered cannabis to ...

Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

Out-of-hospital cardiac arrest (OHCA) represents a critical challenge for emergency medical services, with the necessity for rapid and accurate prediction of defibrillation outcomes to enhance patient ...

Spinal health forms the cornerstone of the overall human body functionality with the lumbar spine playing a critical role and prone to various types of injuries due to inflammation and diseases, ...

. ├── README.md ├── classifier_env.yaml ├── dataset │ ├── README.md │ ├── csv │ │ ├── cpp_dataset.csv │ │ ├── python_dataset.csv │ │ └── sample250_problem_list.csv │ ├── data_extraction.ipynb │ ├── ...

Works Well for Clear Margin of Separation If the two classes (Malignant vs Benign) are well-separated, SVM performs strongly by maximizing the margin between them. Robust to Overfitting (with Proper ...

Abstract: Support Vector Machine (SVM), a robust machine learning algorithm, exhibits exceptional efficacy in addressing image multi-classification challenges. This paper aims to discuss the image ...

Abstract: Applying Support Vector Machine (SVM) theory to hyperspectral images classification can significantly mitigate the decline in classification performance caused by the curse of dimensionality ...