Sentence examples for multiple data mining from inspiring English sources

This chapter reveals that the Java Data Mining (JDM) standard defines Java interfaces to enable application designers and developers to develop comprehensive data mining solutions that are also portable across multiple data mining engines (DMEs).

[6 10] Turning this large volume of information into knowledge could be performed in multiple ways using multiple data mining procedures.

Our approach fits better with our processing pipeline, where multiple data mining algorithms are applied to derive different views, such as those in this paper.

They consider ground-truth messages as training data and test multiple data mining models, including Naïve Bayes, Support Vector Machines (SVM), and Decision Trees.

In addition to the availability of the Official Gene Set (OGS1.0), which includes the genome assembly as well as transcript and protein sequences from our genome annotation, SWFBase incorporates multiple data mining and visualization tools that allow those researching to retrieve and visualize the D. suzukii genome data and OrthologID-generated gene orthology and phylogenetic results of interests.

We analyzed the data with multiple data-mining tools, including the Web Gene Ontology Annotation Plot (WEGO), IDEG6 and the Kyoto Encyclopedia of Genes and Genomes (KEGG).

The characteristics of MSMiner include the ability to support multiple data sources and data mining strategies, additional organizational flexibility in regard to data and mining strategies, and the powerful expansibility of data mining tasks.

The first package would include the wiretap authorities as they existed pre-encryption, but would lack the new techniques for location tracking, confederate identification, access to multiple databases, and data mining.

In the next few years, experts like Tuzhilin predict, we'll see the convergence of multiple disciplines, including data mining, artificial intelligence, psychology, marketing, economics, and experiential design theory.

Applications to multiple-sequence alignment, data mining, and benchmark functions have been performed so as to put forward the performance of developed computational method.

The future winners in the wearables space will have two ace cards in their hands: one is a year or more lead-time in using unique or multiple sensor types in the device; the second is the data science know-how to correlate across multiple data streams to mine for richer insights.