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To assess whether our imputation strategy would yield similar benefits in African populations outside the HapMap 3 set, we performed additional cross-validations in a Gambian dataset from the Malaria Genomic Epidemiology Network (MalariaGEN; Malaria Genomic Epidemiology Network 2008).
Additional cross-validation was performed with an independent microarray data set [ 10].
To remove this bias in testing the validity of the decision trees, an additional cross-validation procedure was performed using 1000 iterations of 100 MDD participants randomly chosen across both cohorts.
To eliminate the possibility of artifacts due to sequence selection bias, additional cross-validations were performed by pooling the bootstrap, positive, and negative sets, and filtering to remove redundant sequences at sequence match levels of 80%, 60%, or 40% using the CD-hit program [ 29].
However, to ensure that the treatment of replicate cell line samples as independent samples in our model did not result in cross-validation bias, we performed additional internal validation experiments.
As additional validation of the clustering results, we perform a cross-validation of the clustering process as follows.
To validate and assess our models we performed tenfold cross-validation and nested cross-validation protocols.
The models refinement procedure and their validation were performed by cross-validation.
The models refinement procedure and validation were performed by cross-validation.
The validation of the model was performed by cross-validation method.
Internal validation of results was performed using cross-validation.
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