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 ...

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 ...

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 ...

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 ...

The exponentially increasing amounts of data being generated each year make getting useful information from that data more and more critical. The information frequently is stored in a data warehouse, ...

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 ...

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 ...

“As our connected world continues to expand thanks to the Internet of Things, information related to our lives is increasingly linked through cloud-based networks, creating a host of new requirements ...