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To feed the next module (classification), we sampled the mean value, standard deviation, root mean square (RMS) and FFT amplitude of the received signals.
To the best of our knowledge, existing approaches rely on fully automated module classification and do not provide a way to incorporate extra knowledge during the classification process.
Description of data: Module classification of recently wild-derived zebrafish transcriptomes.
A randomization of protein module classification eliminates the significant CAI differences across the modules (table 1).
Randomizing the module classification of substrates eliminates the differences in evolutionary rate among the modules (table 1).
In the end, the module classification is discrete but doesn't really quantify the divergence in expression very well.
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The complete list of top IRESs predictions, their module classifications, connectivity degrees and descriptions are presented in Additional file 2. Module 1: Heme biosynthesis.
These module classifications provide an opportunity to study the association between anatomical parameters and connection features at a larger-scale level of cortical organization.
Hence, our proposed system contains mainly two modules: the enrichment module and classification module.
To provide illustrative examples of the definitions listed below, a machine learning application of software module defect classification is used where a learner is trained to predict whether a software module is defect prone or not.
Referring to the software module defect classification application, an example of marginal distribution differences is when the source software program is written for a user interface system and the target software program is written for DSP signaling decoder algorithm.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com