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For one, validation was achieved by addition of only one new cell action coupled with replacement of one axiom.
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For example, one validation pool had 0 positive and 30 negative samples, another had 1 positive and 29 negative samples, etc.
Then these found motifs were used to pinpoint TFBS (using CisFinder) on the other two partitions - One validation partition for determining appropriate parameters, and the other partition for making comparison over algorithms.
To make a comparison between 3D segmentation results with and without post-processing (PP), average DI and standard deviation is 0.89 ± 0.6 (with PP) vs. 0.87 ± 0.6 (without PP) for one slice validation against STAPLE TS.
Tables 4 and 5 show confusion matrices for one cross-validation run of the hierarchical and direct approach respectively.
Then, we run the DE and analyse the results five times using three of the sets for learning, one for validation, and one for testing.
SNPs with fixed observed genotypes or estimated B-allele dosages for one or more validation groups were removed.
Therefore, SNPs with fixed observed genotypes or estimated B-allele dosages for one or more validation groups were removed.
CONSTANT indicates that at least one reviewer has given all test items a constant rating for one of the validation questions.
To calculate imputation accuracy, all SNPs with fixed observed genotypes or estimated B-allele dosages for one or more validation groups were removed.
The ability of a Random Forest classifier trained on one ligand to reject binding sites of different ligands was assessed by comparing Random Forest scores from 10-fold cross-validation for one ligand (ligand 1) with scores from training on all cross-validation data for ligand 1 and then predicting for data from a different ligand (ligand 2).
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