This workflow calls a workflow service which applies a model to data. Data are generated at the Data Generator node, then partinioed using 30% of the data for training and 70% for testing. A Random Forest Learner node is used to perform a prediction on the training data. The prediction model is then transmitted to an external workflow which applies the model to the testing data portion, also transmitted to the external workflow via a Call Workflow Service node. Results for both training and testing are then scored and their accuracy is compared. Finally Is possible to choose whether to append the confidence for the predicted class the confidences for all the other classes.