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Most importantly, the architecture provides the ability to run multiple learner models to be run in parallel and their output displayed back to users in near real-time.
Ensemble learning involves estimating multiple "learner" models on a training data set and predicting unseen observations by a vote or weighted average among the multiple learners (Dietterich 2000).
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This blended model addressed the challenge of coordinating multiple learners from multiple colleges and schedules.
Future research should test multiple learners across multiple datasets using many different feature engineering methods.
Besides, employing multiple learners does not only complicate the system architecture, but also increase training and testing time costs.
Existing chunking systems make use of external knowledge, e.g. grammar parsers, or integrate multiple learners to achieve higher performance.
The best learner found by each study is shown in Table 9, but should not be considered conclusive due to the experiments not thoroughly studying multiple learners.
Meta-learning [20] is loosely defined as learning from information generated by learner(s) and it is applied to coalesce the results of multiple learners to improve accuracy.
In this paper, we present a novel phrase chunking model based on the proposed mask method without employing external knowledge and multiple learners.
Duolingo says its users learn about as well as those who use Rosetta Stone, and that its translations are about as good as those from professional translators (thanks also, of course, to the fact that it can compare multiple translations from multiple learners).
This paper explores the opportunities offered by Mining@Home for coping with the discovery of classifiers through the use of the bagging approach: multiple learners are used to compute models from the same input data, so as to extract a final model with high statistical accuracy.
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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