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the threshold refers to the confidence value of the prediction. You can read it like this: if the confidence of the example to be positive is greater than the threshold, the example will be classified as positive, if the confidence is below the threshold, it will be classified as negative.
You can experiment with thresholds by using the Create Threshold and Apply Threshold operators after classification, but before applying the Performance operator.
If you have further questions, don't hesitate to ask
the threshold refers to the confidence value of the prediction. You can read it like this: if the confidence of the example to be positive is greater than the threshold, the example will be classified as positive, if the confidence is below the threshold, it will be classified as negative.
You can experiment with thresholds by using the Create Threshold and Apply Threshold operators after classification, but before applying the Performance operator.
If you have further questions, don't hesitate to ask
All the best,
Marius