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We made our predictions based on that much.
Methods for evaluating predictions based on machine learning.
But all predictions based on computer projections have inherent uncertainties.
They just spit out predictions based on the data fed into them.
This exceeded predictions, based on last year's results, that around 7% would get an A*.
As a result, even UNS predictions based on the correct vote shares are far from perfect.
In addition, predictions based on the analytic solutions were compared with predictions based on computational methods.
The election forecasts are in fact predictions, based on various and varied statistical models.
Google Now makes predictions based on a person's location, e-mail and Web search history.
Then, with this, you can update your predictions based on other changing values of expectation.
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*Predictions based on multiple regression model with random effects.
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