Anomaly detection can be used to determine when something is noticeably different from the regular pattern. BYU professor Christophe Giraud-Carrier, director of the BYU Data Mining Lab, gave the ...

Data mining and knowledge discovery represent an integrative process through which large, complex and heterogeneous datasets are transformed into actionable insights. This field encompasses a series ...

Data mining is an analytical process designed to explore and analyze large data sets to discover meaningful patterns, correlations and insights. It involves using sophisticated data analysis tools to ...

Experts have developed a new way of mining data from climate data sets that is more self-contained than traditional tools. The methodology brings out commonalities of data sets without as much ...

Data mining has been defined as “the nontrivial extraction of implicit, previously unknown, and potentially useful information from data”. 1 In areas other than the life sciences and healthcare, data ...

Data mining has evolved from the esoteric domain of the mathematician to the expert statistician’s programming and workbench tools and, at last, to the realm of widely accessible business applications ...

The second step in data mining process is the application of various modeling techniques. These are used to calibrate the parameters to optimal values. Techniques employed largely depend on analytic ...

Data mining isn’t just techno-speak for messing around with a lot of data. Data mining doesn’t give you supernatural powers, either. Data mining is a specific way to use specific kinds of math. It’s ...

Dr. Chris Hillman, Global AI Lead at Teradata, joins eSpeaks to explore why open data ecosystems are becoming essential for enterprise AI success. In this episode, he breaks down how openness — in ...