Discretization algorithms serve as a critical pre-processing step within data mining and machine learning, transforming continuous attributes into discrete categories to enhance the ...

This article reviews and advances existing literature concerning digital twin modeling, multi-sensor fusion technology, and data mining algorithms in cloud and edge computing-based smart city ...

Faulty data mining makes seeking of decisive information akin to finding a needle in a haystack. Here are some tips to tweak your data mining exercises.

Semi-supervised learning uses both tagged and untagged data to fit a model. In some cases, such as Alexa’s, adding the untagged data actually improves the accuracy of the model. In other cases ...

This suite includes both unsupervised (B-SOiD) as well as supervised algorithms (A-SOiD) which learn behaviors and add interpretability to pose estimation data. We simultaneously recorded from neurons ...

Here are the differences between supervised, semi-supervised, and unsupervised learning -- and how each is valuable in the enterprise.