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Cross-validation is a technique wherein the total data set is split into k equally sized parts, called k folds.
However, the size of the predicted subset (by i-rDNA) as a proportion of the total data set is observed to be around 10-15%.
An increase of 20 30% in A/T at these positions compared to the total data set is evident for most species.
In order to obtain robust estimates of the internal construct validity of the scale, the total data set is randomised into two further sets of approximately 50% of cases.
Similar(56)
By weighting the type-specific average values by the ratio 56:446 (see Table 2), the descriptive statistics of the total data set were calculated.
Their data, 6% of the total data set, are included in all the analyses.
Their data, 6.6% of the total data set, are included in all analyses.
Significant differences in gene expression for the "total" data set were determined, and a 2-fold change with a P value less than 0.05 was considered significant.
Genes were first sorted by CR value order, and then the CRs of the original total data set were compared with those of permuted data.
The accuracy of estimation for the SVM analysis increases with the increases of number of effective parameters and the ratio of training data sets to total data sets being considered in the calculation of SVM modeling.
Each tree starts with the total data set, which is split into smaller and more homogeneous groups to fit models for predicting the outcome from the measured proteins.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com