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

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Classification algorithms learn how to assign class labels to examples (observations or data points), although their decisions can appear opaque. A popular diagnostic for understanding the decisions ...

Linear Trees combine the learning ability of Decision Tree with the predictive and explicative power of Linear Models. Like in tree-based algorithms, the data are split according to simple decision ...

In this tutorial, we’ll build on the foundation laid in the “Arduino-Based Solar Power System Using Python & Machine Learning, Part 1” project by exploring how to intelligently select and use machine ...

Java is not the first language most programmers think of when they start projects involving artificial intelligence (AI) and machine learning (ML). Many turn first to Python because of the large ...

Gradient boosted decision tree (GBDT) is a popular machine learning algorithm. Current open-sourced GBDT implementations are mainly designed for single output. When there are multiple outputs, they ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

Abstract: This study aimed to develop a new method for combining Sentinel-2 and PlanetScope (PS) imagery. The normalized difference vegetation indices (NDVI) data were retrieved from the Earth ...