The phrase "data mining application" is correct and usable in written English.
You can use it whenever you are referring to an application that uses data mining technology. For example: "The company recently launched a new data mining application to better analyze customer trends."
Finding the right data representation is essential for virtually every data mining application.
The effectiveness of the algorithm is illustrated with the warranty data mining application from the automotive industry.
Ideally, a data mining application would generate all the patterns existing in the database (the "completeness" criterion), as fast as possible.
Presented is a novel interactive visual data mining application, SysNet that provides an interactive environment for the analysis of high data volume molecular expression information of most any type from biological systems.
The objective of this research is to employ this approach to develop an interactive visual data mining application for 'omics expression data analyses that combines interactive visualization and statistical data mining.
Clustering (Hartigan 1975; Jain and Dubes 1988; Oliveira and Pedrycz 2007) is a widely used technique in data mining application for discovering patterns in underlying data, which partitions the input space into K regions depending on some similarity/dissimilarity metric, where the value of K may or may not be known a priori.
Experiments show that the k-modes clustering algorithm using refined initial points leads to higher precision results much more reliably than the random selection method without refinement, thus making the refinement process applicable to many data mining applications with categorical data.
This is a valuable capability in spatial data mining applications.
Oracle orcl uses neural networks in a product called Darwin, software tools for "data mining" applications.
In that context, feature selection is becoming an essential requirement in many data mining applications.
Based on the BCM learning rule, a few data mining applications of neuronal selectivity have emerged.
