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 ...

The Data Science Lab Binary Classification Using a scikit Decision Tree Dr. James McCaffrey of Microsoft Research says decision trees are useful for relatively small datasets and when the trained ...

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 ...

With the massive expansion of information technology, the demand for data mining also grew hugely. But data mining — or the process of wading through huge amounts of data and finding what you consider ...

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 ...

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 ...

For better accountability, we should shift the focus from the design of these systems to their impact. Describing a decision-making system as an “algorithm” is often a way to deflect accountability ...

The Journal of Developing Areas, Vol. 50, No. 5, Special Issue on the Kuala Lumpur Conference, November 23-24, 2015 (2016), pp. 371-381 (11 pages) The growing interest in the credit industry resulted ...