A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...

An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...

ABSTRACT: Lung cancer stands as the preeminent cause of cancer-related mortality globally. Prompt and precise diagnosis, coupled with effective treatment, is imperative to reduce the fatality rates ...

ABSTRACT: Egg loss is one of the major problems in the egg hatching industry. This study aims to support farmers in optimizing their egg hatch through the development of a prediction model. This is to ...

Adaptive algorithms have immensely advanced, becoming integral for innovation across multiple industries. These intelligent systems adjust content and strategies to improve the experiences of users by ...

The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...

Implementations of perceptron algorithm with 2 hidden layers, learning vector quantization, k-means clustering algorithm, for the course Computational Intelligence @uoi ...

Abstract: The one-bit quantization with time-varying thresholds has been studied in the field of compressed sensing and SAR imaging. The Perceptron Learning Algorithm (PLA) uses a sign function as its ...

In a world saturated by artificial intelligence, Machine Learning, and over-zealous talks about both, it is important to understand and identify the types of Machine Learning we may encounter. For the ...