The emerging convergence of AI-first design principles and environmental consciousness is reshaping how we think about ...

Abstract: The density peaks clustering algorithm is one of the density-based clustering algorithms. This algorithm has several advantages, including not requiring a preset number of clusters, ...

The CPU and GPU confusion matrices are nearly identical. The prediction agreement between both implementations reached 99.82%, showing that the CUDA implementation preserved the classification ...

Abstract: In multi-label learning, each instance in the training set is associated with a set of labels, and the task is to output a label set whose size is unknown a priori for each unseen instance.

This project uses Machine Learning to classify Iris flowers into three different species based on their physical measurements. The classification is performed using the K-Nearest Neighbors (KNN) ...

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.

The subthalamic nucleus contains subpopulations with different contributions to deliberative decision-making based on noisy evidence and reward-driven preferences.

The primary endpoint was 3-month mortality due to all causes. Six ML algorithms (Extreme Gradient Boosting [XGBoost], logistic regression (LR), Light Gradient Boosting Machine [LightGBM], random ...

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...

The ever-growing world population is over-stressing the available resources leading to several social, economic, and environmental issues. The world is facing challenges related to the availability of ...