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

Data mining techniques have been widely used for extracting knowledge from large amounts of data. Monitoring deforestation is utmost important for the developing countries. Classification of ...

A guide to what data mining is, how it works, and why it's important. Big data is everywhere we look these days. Businesses are falling all over themselves to hire 'data scientists,' privacy advocates ...

Data mining has its origins in conventional artificial intelligence, machine learning, statistics, and database technologies, so it has much of its terminology and concepts derived from these ...

Real-world predictive data mining (classification or regression) problems are often cost sensitive, meaning that different types of prediction errors are not equally costly. While cost-sensitive ...

Alexandra Twin has 15+ years of experience as an editor and writer, covering financial news for public and private companies. Natalya Yashina is a CPA, DASM with over 12 years of experience in ...

The visual data mining process, seen in the first part of this two-part article, revealed patterns in four dimensions between cumulative gas well production and independent variables. "Jump ...

Jeremy Kun does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their ...

Dermatologists typically classify skin lesions based on multiple data sources. Algorithms that fuse the information together can support this classification. An international research team has now ...