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4. CASE Switch

CASE Switch
Workflow: CASE Switch The goal of this workflow is to classify the car makers based on the cars they produce. The target class is the "make" column.The calssification model could a decision tree, a pNN, or a manual set of rules: this is the user choice.The choice for the classification model is made in the Value Selection Widget node. Depending on which predictive model has been chosen, the corresponding branch of the CASE block is activated and the model is trained and applied. Predictions are collected in the CASESwitch Data (End) node and performances on the training set are evaluated at the end with a Scorer node. The trick is to produce predictions in an output column named the same on all thebranches. The selected model is collected with a CASE Switch Model (End) node and written to file. collect data withpredictionsFollow dedicated branchaccording to selected predictive modelpredicting "make"collect modelgenerate predictions on training setgenerate predictionson training setlist ofavailablepredictive modelspredicting "make"manual rule setFlow Variable: ClassificationModelselect ClassificationModeEvaluate Modelcars-85.csv CASE SwitchData (End) CASE SwitchData (Start) PNN Learner (DDA) CASE SwitchModel (End) Decision TreePredictor PNN Predictor Table Creator DecisionTree Learner Rule Engine Rule EngineVariable Value SelectionWidget Scorer (JavaScript) CSV Reader Workflow: CASE Switch The goal of this workflow is to classify the car makers based on the cars they produce. The target class is the "make" column.The calssification model could a decision tree, a pNN, or a manual set of rules: this is the user choice.The choice for the classification model is made in the Value Selection Widget node. Depending on which predictive model has been chosen, the corresponding branch of the CASE block is activated and the model is trained and applied. Predictions are collected in the CASESwitch Data (End) node and performances on the training set are evaluated at the end with a Scorer node. The trick is to produce predictions in an output column named the same on all thebranches. The selected model is collected with a CASE Switch Model (End) node and written to file. collect data withpredictionsFollow dedicated branchaccording to selected predictive modelpredicting "make"collect modelgenerate predictions on training setgenerate predictionson training setlist ofavailablepredictive modelspredicting "make"manual rule setFlow Variable: ClassificationModelselect ClassificationModeEvaluate Modelcars-85.csv CASE SwitchData (End) CASE SwitchData (Start) PNN Learner (DDA) CASE SwitchModel (End) Decision TreePredictor PNN Predictor Table Creator DecisionTree Learner Rule Engine Rule EngineVariable Value SelectionWidget Scorer (JavaScript) CSV Reader

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