DBSCAN is a well-known density based clustering algorithm capable of discovering arbitrary shaped clusters and eliminating noise data. However, parallelization of DBSCAN is challenging as it exhibits ...

A good way to see where this article is headed is to take a look at the screenshot in Figure 1 and the graph in Figure 2. The demo program begins by loading a tiny 10-item dataset into memory. The ...

Recent advances in data mining and mathematical modelling have increasingly influenced the development of sophisticated algorithms across diverse application domains. By extracting hidden structures ...

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 ...