Here, appropriate data mining algorithms are selected based on the goal of the mining — e.g., classification, regression, clustering, etc. Different algorithms are better suited for different ...

Computer applications with data mining algorithms are most frequently used to perform data mining. From there, the results are often translated into visual or statistical representations for ...

The main topics include an overview of databases, data warehouses and data mining technology, data warehousing and on line analytical process (OLAP), concept mining, association mining, classification ...

Data mining is the use of computers to pour through vast quantities of data to draw conclusions or predict outcomes. We explain what it is and how it's used.

Data Quality Issues: The effectiveness of data mining heavily depends on the quality of the data being analyzed. Incomplete, inaccurate, or ambiguous data can lead to misleading results.

Before you can apply data mining algorithms, you need to build a target data set. One common source for data is a data mart or warehouse. You need to perform preprocessing to be able to analyze ...

A new data-driven technique for obstacle avoidance in autonomous vehicles is reported in the International Journal of Vehicle ...

JO: In addition to constructing the data refinery, Descartes Labs has built a method and algorithms to select the ‘barest-earth’ pixel for each of the ASTER and Sentinel-2 datasets, which are ...

References [1] Use of data mining algorithms to predict body weight of Dorper sheep Breed in two selected villages of Lepelle-Nkumpi local municipality in Limpopo province, South Africa. Smart ...