Prediction and Modeling Operator Pairings
In general, the Classification Modeling operators are followed in a workflow by a Classifier operator, and the Regression Modeling operators that predict a value are followed by a Predictor Operator.
However, a Predictor operator can also be applied to Classification models in order to return the value with the highest probability.
The few exceptions are for modeling techniques such as Collaborative Filtering, Time Series, EM Cluster, PCA, and LDA that have their own specialized Predictor operator (shown in the following table). See Prediction Operators for more information about the classifiers and predictors.
The following table summarizes which Prediction operators can follow Modeling operators (to apply the appropriate modeling algorithms).
| Modeling operator | Next operator | Exception |
|---|---|---|
| ARIMA Time Series | n/a | Time Series Predictor |
| Alpine Forest | Classifier or Predictor | n/a |
| Alpine Forest Regression | Predictor | n/a |
| Association Rules | n/a | n/a |
| Collaborative Filter Trainer | n/a | Collaborative Filter Predictor, Collaborative Filter Recommender |
| Decision Tree | Classifier or Predictor | n/a |
| Elastic Net Linear | Predictor | |
| Elastic Net Logistic | Classifier or Predictor | |
| Generalized Linear Regression Models | Predictor | |
| Gradient Boosting Classification | Classifier | n/a |
| Gradient Boosting Regression | Predictor | n/a |
| K-Means | Classifier* | n/a |
| Linear Regression | Predictor | n/a |
| Logistic Regression | Classifier or Predictor | n/a |
| Naive Bayes | Classifier or Predictor | n/a |
| Neural Network | Classifier or Predictor | n/a |
| PCA | n/a | PCA Apply* |
| SVM Classification | Classifier or Predictor | n/a |
*PCA Apply operator and the Classifier for K-Means are used only within Hadoop workflows.