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Ethnicity is very important to the predictive models; risk assessments developed using regional data outperform generalised global assessments.
Furthermore, both studies showed that compound classifications based on in vivo data outperform classifications based on gene sets from the literature ('expert knowledge').
In DE analysis, RNA-Seq data outperform microarray data in terms of the accuracy of measuring gene expression levels and, therefore, RNA-Seq can potentially detect more differentially expressed (DE) genes [ 12].
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The results show that the vector normalization method (number 5) applied directly on the signal data outperforms all other methods.
The proposed method without parameter tuning (that is, α=n=1), which suppressed the reverberation in both training and test data, outperformed all the other methods under all reverberant environments.
It was found that the statistical models that combined the tree-ring reconstructed data with the observed data outperformed those that did not, in terms of reducing the root mean squared errors.
In addition, with the comparison between MNF images for lithological classification of Sentinel-2A and ASTER data, it was demonstrated that Sentinel-2A data outperformed ASTER in lithological mapping in the Shibanjing ophiolite complex.
Through inspection of the results it was found that although the model built on transformed data outperforms the model built on raw data, no significant differences were found between the forecast accuracies of the three examined models.
In general, the fine resolution SSURGO data outperformed the coarse resolution STATSGO data for county-scale crop-yield simulation, and within STATSGO, the area-weighted approach provided more accurate results.
Their results showed training a deep CNN from character-level data outperformed networks trained on data with features generated with bag-of-words, bag-of-centroids and the deep learning approach Word2Vec.
It also provides the ability to detect some new kinds of attacks (for which there was no previous information in the testing data), outperforming other works in this aspect.
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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