In the logistic regression workflow, which Rapid Miner operator connects the training data stream with the scoring data stream?

• A. Apply Model
• B. Filter Examples
• C. Join
• D. Normalize

Answer: (A)

In this step, you need to take the model you learned from training and use it to make predictions on new data. The operator that does exactly that in RapidMiner is the one that takes the trained model and a scoring data set and outputs the predicted labels (and often probabilities) for each new example. This is how the trained logistic regression model is actually applied to unseen data to produce scores or class predictions.

So, the right choice is the operator that bridges the training stream to the scoring stream by applying the learned model to the new data. The other operators perform different tasks: Normalize scales features, Filter Examples trims the data, and Join would merge datasets but not perform the scoring step itself.