This subprocess provides the labeled ExampleSet. This Example Process starts with a Subprocess operator. Tutorial Processes Creating and Applying thresholds The predictions of the input ExampleSet are changed according to the threshold given at the threshold port and the modified ExampleSet is delivered through this port. Frequently, the Create Threshold operator is used for providing threshold at this port. The threshold is provided through this input port. The ExampleSet should have label and prediction attributes as well as attributes for confidence of predictions. This input port expects a labeled ExampleSet. In contrast, hard classification bypasses the requirement of class probability estimation and directly estimates the classification boundary. In particular, a soft classification rule generally estimates the class conditional probabilities explicitly and then makes the class prediction based on the largest estimated probability. This can be easily understood by studying the attached Example Process.Īmong various classification methods, there are two main groups of methods: soft and hard classification. If the confidence for the second class is greater than the given threshold the prediction is set to this class otherwise it is set to the other class. Mostly the Create Threshold operator is used for creating thresholds before it is applied using the Apply Threshold operator. The threshold is provided through the threshold port. The Apply Threshold operator applies the given threshold to a labeled ExampleSet and maps a soft prediction to crisp values.
SynopsisThis operator applies a threshold on soft classified data. You are viewing the RapidMiner Studio documentation for version 8.0 - Check here for latest version Apply Threshold
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