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Experimental results reveal the high accuracy and suitability of the proposed approach, driving the selection of most suitable and scalable classification pipelines and stimulating clinical validations.
PLANET is used to construct scalable classification and regression trees, as well as ensembles of these models.
Furthermore, it is a highly scalable classification algorithm, eliminating the need for separate cross validation and error estimation, as these procedures are part of the internal classification routine (for details on the procedure and the error estimates we refer to Additional file 1).
FunCat is a hierarchically structured, scalable classification system enabling the functional assignment of proteins from any genome according to their physiological role, or metabolic pathway.
The results show comparable or better accuracy than existing methods, and even with novel genomes in a sample, accurate and scalable classification is obtained in the vast majority of cases.
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In short, it is entirely a novel topology, an unprecedented approach for dynamic, content/data adaptive and scalable audio classification.
Results: A method is presented to shift computational costs to an off-line computation by creating a taxonomy/genome index that supports scalable metagenomic classification.
Scalable metagenomic taxonomy classification using a reference genome database.
Naive Bayes classifiers provide an efficient and scalable approach to supervised classification problems.
To show DAN2 as an effective and scalable alternative for text classification, we present comparative results for the Reuters-21578 benchmark dataset.
Our software provides an easy to use and scalable alternative to taxonomic classification of marker genes that is applicable to any nucleotide fragment.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com