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A curves similarity determination method was incorporated for data training.
Elapsed time for data training is shown in Table 2.
Several correlation metrics that use data training are described.
The paper proposed a dual stage multi-resource data training scheme using multi-objective genetic algorithm.
We want to use data training and pattern recognition to at least group alerts and surface things that matter most.
In [12], both time domain and frequency domain algorithms with data training have been investigated.
Labeled data training is called supervised training, where the correct outcome is labeled and used as feedback.
The designed ANN, after the selection of a proper data training set, allows automatic detection of weld defects.
Data training is achieved through the Monte-Carlo Simulation, and the prediction model is validated through error analysis.
It shows an example when MapReduce is applied multiple times to perform data processing, data training, and testing.
Indeed, being overconfident of large sample sizes is one of the most common statistical blunders we see as a big data training company.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com