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It has been observed that learning multiple related tasks simultaneously often improves modeling accuracy and leads to better feature selection, especially in cases where each task has very limited number of training samples.
It has been observed that learning multiple related tasks simultaneously often improves predicted accuracy [ 54].
Multi-task learning technologies have been developed to be an effective way to improve the generalization performance by training multiple related tasks simultaneously.
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The emphasis here is not on investigating a preferably extensive set of problems as in algorithm selection; it is mostly used for a smaller selection of multiple related learning tasks.
For multiple related pathogenic species (intraspecies), once the complete genome sequences are available, it is a desirable task to predict global vaccine targets that are conserved among all genomes.
Other packages may focus on a specific task or a set of related tasks.
Workers specialise in related tasks according to their sizes.
Here, there are two separate but related tasks.
For example, for Subject 8, with placebo during the phonological task, three task-related ICs (IC #2, #7, and #18) were selected, and are displayed in the first three images of Figure 4. Whenever a subject showed multiple task-related ICs for a condition, another step was applied to summarize these sources in order to obtain the individual summary map.
Moreover, this consisted of multiple aspects of self-reported occupational exposure, including the duration and location of various disaster-related tasks and the experience of potentially stressful events during these tasks.
We included multiple aspects of level of exposure, such as the duration and the potential psycho-traumatic character of disaster-related tasks, as it is unknown which aspect of occupational exposure to disasters is relevant for long-term health.
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CEO of Professional Science Editing for Scientists @ prosciediting.com