"accuracy on dataset" is a grammatically correct and usable phrase in written English.
It can be used when discussing the level of correctness or precision achieved when applying a model or algorithm to a specific dataset. Example: The machine learning algorithm had an overall accuracy of 85% on the training dataset, but only 75% accuracy on the test dataset.
Among these strategies, the combination of the SPIC metric and the Smith-Waterman algorithm (SPIC/SW) with gap open equal to 1 achieves the highest accuracy on Dataset-1.
The results for the simulated datasets show clearly that all the methods produce trees with about the same accuracy on datasets with very dense scaffolds, but differ substantially in terms of accuracy on the datasets with sparser scaffolds.
We obtained high classification accuracy on datasets obtained from two different sites, which indicates reproducibility of our results and robustness of our approach.
On the 500-taxon datasets, QMC(Exp+TSQ) had a slight advantage over gMRP on the sparse scaffold datasets, but essentially the same accuracy on datasets with the two densest scaffolds.
To calculate their accuracies on dataset D, we trained those classifiers on dataset B and tested on dataset D. To calculate their accuracies on dataset E1 and E2, we performed LOOCV analysis.
The cascaded classifiers did not exhibit significant compromises in their generalization ability and in fact produced evidence of improved accuracies on datasets with biased-class distributions.
The accuracies on Datasets 4 and 5 are 82.75% and 80.42%, respectively, which shows DCN-based method has a decent sensitivity to distinguish and classify closely-related species, i.e. in the deeper level of the phylogenetic tree, as dataset 4 contains only genomes from Bacterial Division 12, and dataset 5 contains both Division 12 and 13.
A high R-value for a dataset indicates that the dataset contains wide overlapping areas among its categories, and classification accuracy on the dataset may become low.
Weighted majority voting based on base classifiers' cross validation accuracy on training dataset is used as the combination mechanism.
