eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

Incomplete data affects classification accuracy and hinders effective data mining. The following techniques are effective for working with incomplete data. The ISOM-DH model handles incomplete data ...

Predictive analytics enables you to develop mathematical models to help you better understand the variables driving success. Predictive analytics relies on formulas that compare past successes and ...

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 ...

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 ...

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 ...

Despite lithium’s role as the critical raw material to advance global decarbonisation strategies, the controversial nature of the sustainability of lithium operations is rising to the fore, highlights ...