Examples of using Predictive models in English and their translations into Tagalog
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One approach is to use climate or other predictive models.
However, one major concern with predictive models being used to allocate resources is that the models have the potential to reinforce existing biases.
Many researchers already know“garbage in,garbage out,” and with predictive models it can be“bias in, bias out.”.
In New York City, these predictive models were built by city employees, but in other cases, one could imagine that they could be created or improved with open calls(e.g., Glaeser et al.(2016)).
See Barocas and Selbst(2016) and O'Neil(2016)for more on the dangers of predictive models built with biased training data.
At MIT, for example, scientists are using nanoparticles to transport time-release anticancer drugs directly to cancerous cells, developing drugs that fight diseases without damaging healthy tissues and cells, andimproving new predictive models of disease.
They estimated that the predictive model that won the open call would improve the productivity of restaurant inspectors by about 50%.
Glaeser and colleagues estimate that the predictive model that won the open call would improve the productivity of restaurant inspectors by about 50%.
Amplified asking using a predictive model to combine survey data from a few people with a big data source from many people.
For example, a researcher with a million human classified galaxies can build a predictive model that can then be used to classify a billion or even a trillion galaxies.
In fact, one policing model, predictive policing, can exacerbate racial tension between law enforcement and African-American communities.
Then, he used nine of the chunks to train his model, and the predictive performance of the trained model was evaluated on the remaining chunk.