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This indicates the distinct phenotypes clustered by the extracted predictor are significantly different from each other.
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The median-based consensus human predictor was significantly better than 13 out of the 17 individual humans with respect to its prediction errors, even for a small dataset on which statistical significance is hard to demonstrate.
The only such instances of significance are that the consensus predictor is significantly different from PLS and SGD at the 5% level, and MLP is also significantly different from SGD. Machine learning scripts used are given in Additional file 7. A total of 22 answer sets were received from human participants, a response rate of 9.6%.
We also show that the integrated predictor is significantly better than each individual predictor.
Tumor stage and the 17 probe set prognostic predictor were significantly related to the hazard of death.
Coefficients for the eccentricity predictor were significantly positive for all but one comparison (V1 hV4 inter-hemisphere) (ps < 0.05, FDR corrected).
The consensus predictor is significantly better than all the Scansite predictors and ELM, based on the MCC scores obtained for the BLIND dataset (P < 0.05).
Before the age of 3, the slope of the linear predictor was significantly greater than zero (P = 0.0025), i.e. the estimated level of OUC increased.
Our large-scale tests on the human genome show that the meta predictor is significantly superior in terms of sensitivity and specificity, as compared to the individual PPPs.
Coefficients for the polar angle predictor were significantly positive for most intra-hemisphere comparisons, but only for a few inter-hemisphere comparisons (ps < 0.05, FDR corrected).
Across subjects, the coefficients for the overlapping RF predictor were significantly positive for all intra-hemisphere, intra-areal comparisons as well as for most other comparisons (ps < 0.05, FDR-corrected).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com