Abstract: There are many application scenarios involving imbalanced datasets, whereas many traditional machine learning methods have limited ability to adapt to this kind of data. These methods ...

Florida State football broke a four-game losing streak with a 42-7 win over Wake Forest. Head coach Mike Norvell praised the team for playing "complementary football" in the victory. Norvell hopes the ...

The goal of this project is indentify fraudulent transactions while minimizing false positives (non-fraudulent transactions flagged as fraud) and false negatives (missed fraudulent transations). The ...

A pioneering study reveals how archaeologists' satellite tools can be repurposed to tackle climate change. By using AI and satellite LiDAR imagery from NASA and ESA, researchers have found a faster, ...

Thank you for this wonderful repo! I'm currently using emlearn to run a Random Forest classifier. I noticed that the generated code uses if-else conditions and return <class> statements to perform ...

ABSTRACT: In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat ...

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.

Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral and ...

President Trump on Wednesday announced tariffs on practically every foreign country (and some non-countries), ranging from a 10 percent minimum all the way up to 50 percent. The economic fallout has ...

The New Jersey State Interscholastic Athletic Association’s executive committee met for its monthly meeting in Robbinsville on Wednesday and discussed several key topics, including a likely change to ...