"In order to be efficient on datasets with a very large number of categories, fastText uses a hierarchical classifier, in which the different categories are organized in a tree, instead of a flat structure (think binary tree instead of list)," said Facebook authors Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov in a post.
Numerical results indicate that the proposed CMAC NN classifier is efficient for tested datasets.
The pipeline is computationally efficient, supporting processing datasets that consist of tens of thousands of peaks.
However, they are not efficient for large datasets.
Calculating all possible itemsets or association rules is not computationally efficient for large datasets and rarely useful for life sciences.
Cox regression is routinely used for epidemiological cohort studies of censored data but is less efficient when large datasets are analyzed.
For example, the heuristic OTU clustering algorithm Uclust applied here to construct HITdb is slightly less robust than the UPGMA method [ 31] but efficient with large datasets.
Therefore, it is not efficient for huge datasets like those produced in genome-wide methylation analyses with average coverage depths ≥10X and genome size ≥1000 MB.
In recent years, several next-generation sequence assemblers have been developed to deal with specific features such as read length, uneven genome coverage values within datasets, efficient managing of computational resources and highly mutational sequence reads.
However, the large number of such fixpoints present in a typical dataset requires efficient computation to make analysis tractable, particularly since any particular fixpoint may be computed many times.
Using the reliable dataset an efficient group contribution (GC) model was developed, which employs a total of 35 functional groups to estimate the temperature-dependent viscosities of F-ILs.
