Interpretability of Support Vector Machine (SVM) or Neural Networks (NN) models, examples of black-box models, is a field of study that has recently gained attention, especially for the significant ...
Abstract: Osteoarthritis (OA) is the most prevalent form of arthritis, commonly affecting the knee joint and characterized by the progressive degeneration of articular cartilage (AC). Among the ...
Valve sent the gaming world into a tizzy when it unveiled a new slate of hardware last month, which includes a small cube dubbed the Steam Machine. Once the initial excitement died down, fans noticed ...
When Valve announced its upcoming Steam Machine hardware last month, some eagle-eyed gamers may have been surprised to see that the official spec sheet lists support for HDMI 2.0 output, rather than ...
Excitement abounds for Valve's quirky cuboid, Steam Machine. But the console-PC hybrid sounds awfully a lot like what Microsoft is hoping to accomplish with its next-generation hardware. Even in an ...
Apple’s MLX machine learning framework, originally designed for Apple Silicon, is getting a CUDA backend, which is a pretty big deal. Here’s why. The work is being led by developer @zcbenz on GitHub ...
The stroke deprives person's brain of oxygen and nutrients, which can cause brain cells to die. Numerous works have been carried out for predicting various diseases by comparing the performance of ...
It's not just Intel code — after a period of undeath, Time Capsule's time is coming, with Apple cutting off support for Time Machine backups using the hardware in macOS 27. Time Capsules, Apple's long ...
ABSTRACT: In the field of machine learning, support vector machine (SVM) is popular for its powerful performance in classification tasks. However, this method could be adversely affected by data ...
Objective: Lung adenocarcinoma (LUAD) continues to be a primary cause of cancer-related mortality globally, highlighting the urgent need for novel insights finto its molecular mechanisms. This study ...
The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.