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mining frameworks, including metamodeling and active learning, have been proposed in recent years. Active learning, a …. Successful application of active learning requires an effective metric in order to gauge the informativeness of data. Current … portfolio valuation and investigate the impact of prediction bias in both the modeling and sampling stages of active learning …
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Building predictive models for genomic mining requires feature selection, as an essential preliminary step to reduce the large number of variable available. Feature selection is a process to select a subset of features which is the most essential for the intended tasks such as classification,...
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Process mining techniques allow organizations to extract knowledge from information systems that store process-related data. Process models can be (re)constructed based on process executions, the SOLL and IST position of process executions can be compared, processes can be bench-marked and...
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Background: Over the last 20 years, process mining has become a vibrant research area due to the advances in data management technologies and techniques and the advent of new process mining tools. Recently, the links between process mining and simulation modelling have become an area of...
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