The data mining step is performed using clustering based on rules by states, which integrates the knowledge discovered separately at each step of the process into a single model of global operation of the phenomenon.
In another work, Arroyo et al. (2010) proposed a methodological approach involving a data mining step to validate and improve the results of an agent-based model.
This limitation is strongly related to the data being mined only once, which shifts the required processing power in the data mining step from the scientist who analyses or visualizes the OSM project for gaining general insights to the group or community that runs the data mining server.
The more than three thousand users that have used the application in New York city have generated thousands of mobility and pricing datapoints that have allowed us to perform an additional data mining step that reveals the large potential benefits of big open datasets in the context of urban transport.
This first data mining step should identify some candidate proteins which could be experimentally validated.
CCA can be used for the purpose of dimension reduction prior to a data mining step for knowledge discovery in databases.
Overall 277,033 putative polymorphisms in 138,339 contigs cumulating 55 Mb consensus sequences were identified in a first data mining step using GigaBayes.
The approach, developed to aim at that purpose as depicted in Additional file 4, applied to the repertoire of symbiotic genes, had the advantage to speed up the data mining step, since any source of information was in the same database, allowing us to combine the results of various analyses.
Data-mining steps, including structures and experimental data pre-treatment, QSAR-ready data preparation, and training/test set splitting were performed using KNIME (version 3) [89].
Our study focuses on executing data mining techniques step-by-step and showing intermediate result at every stage to facilitate sense-making.
