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Both multi-label models yielded 70% accuracy in the test set, but considering label interaction lead to more balanced models.
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Under this framework, multiple label interactions can be uncovered by the shared common structure of the input space.
This ability to capture local idiosyncrasies and to uncover informative label interactions are some of the strongest characteristics of ReliefF [18, 20, 33], and it has been recommended as useful when the task can take advantage of strong feature interactions [20.].
For the issue of redundancy, many researchers attempt to explicitly address feature interactions by finding some low-order interactions, i.e. 2-way (one feature and the label) and 3-way (two features and the label) interactions.
The column labeled "interactions" reports the effect estimates when interaction terms are included in the model.
A final model was trained with all available expert labeled interactions using the best parameter setting we found for SMLE.
The aptamer complexes were designed as molecular switches to undergo conformational change and release fluorescent label upon interaction with the flow of the analyte, causing fluorescence decrease.
We label each interaction with an 'inference threshold', defined as the average percentage of sequence identity between the query human protein and homologous structural complexes of the conserved binding site cluster.
We labeled an interaction 'T' (for possible True interaction) if it has two or more 'P' labels; otherwise it was labeled as 'F' (for possible False interaction).
Nodes are colored by class and some edges are labeled by interaction type.
The latter creates a crowding-out effect by means of what could be labelled Schellings' interaction mechanism.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com