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 ...

This article details and expands those concepts associated with mining functions and algorithms by example. Although we discuss higher-level details of the algorithms used to give some intuition about ...

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 ...

Electronic health record (EHR) systems are increasingly being implemented all over the world, but represent a vast, underused data resource for biomedical research. Structured EHR data, such as ...

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 ...

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 ...

TOKYO-- December 1, 2014 --Toshiba Corporation (TOKYO:6502) today announced the launch of three new application processors, the “TZ2100 group,” as the latest additions to its ApP Lite TM family’s ARM ...

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 table below shows my favorite go-to R packages for data import, wrangling, visualization and analysis — plus a few miscellaneous tasks tossed in. The package ...