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As a result, all the data in the training data set, 70 percent of the data in the mining structure, is used for cross-validation.

This process is repeated until Analysis Services has created and tested the specified number of models.

The data that you specified as being available for cross-validation is distributed evenly among all partitions.

, meaning the probability that the predicted state is correct.

If the predict probability exceeds the accuracy bar, the prediction is counted as correct; if not, the prediction is counted as incorrect.

Note You can set a value of 0.0 for the threshold, but the value is meaningless, because every prediction will be counted as correct, even those with zero probability.

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