Examples of using Predictive models in English and their translations into Greek
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Colloquial
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Official
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Medicine
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Ecclesiastic
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Financial
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Official/political
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Computer
for more on the dangers of predictive models built with biased training data.
It uses predictive models to suggest actions to take for optimal outcomes,
create and verify predictive models, plus deploy and refine predictive versions.
The optimization of diagnosis and treatment through the use of novel medical imaging analysis tools and predictive models.
Scientists were able to determine that our brain generates predictive models, based on similar memories and situations.
garbage out,” and with predictive models it can be“bias in, bias out.”.
garbage out,” and with predictive models it can be“bias in, bias out.”.
This move led to a 90% decrease in the duration it takes to build predictive models.
Einstein's theories concerning relativity have so far held up spectacularly as a predictive models.
We claimed earlier that many of the advancements attributed to narrow AI are predictive models conceptually similar to modelling techniques already used in the insurance industry.
develop and verify predictive models, and deploy and refine predictive models.
Currently, Southern States uses its analytics tool to build predictive models for identifying direct mailer opportunities,
Additionally, some of our predictive models show that Fiora will probably benefit from the 2015 preseason changes,
as well as predictive models of the contribution of individual microorganisms to aid in decision-making on food quality and safety.
This year, the percentage of executives that believe they are fully capable of developing predictive models doubled from 4 percent in 2015 to 8 percent in 2016,
So AmEx started looking for indicators that could really predict loyalty and developed sophisticated predictive models to analyze historical transactions
Analysts develop predictive models by training the model on a portion of the data set where the outcome is known,
The percentage of executives who believe they are fully capable of developing predictive models doubled from 4 percent in 2015 to 8 percent in 2016,
will allow us to build predictive models for each of us as individual patients.
which involves complex applications with elements such as predictive models, statistical algorithms