The PMML Ensemble Predictor node takes a pmml document containing an ensemble of other models and executes all of them on the given data. The results from all models are then aggregated using a method specified in the ensemble model. The output contains a column for each prediction of the single models (if set in the settings) and one column with the combined result. Note that ensembles of ensembles are not supported with the exception of Gradient Boosted Trees which are treated base model. It's on the other hand not possible to predict Gradient Boosted Trees models with this predictor, please use the PMML Predictor node or the Gradient Boosted Trees Predictor (PMML) nodes for this task.
Options
Popular Predecessors
PMML Reader17 %- Partitioning8 %
- PMML Reader7 %
- PNN Predictor6 %
- Table to PMML Ensemble5 %
- Decision Tree Learner5 %
- PMML Ensemble Loop End4 %
- Cell to PMML3 %
- Column Filter (PMML)3 %
- PMML Ensemble to Table3 %
Excel Reader (XLS)3 %Model Reader2 %- PMML Predictor2 %
- Reference Row Filter1 %
- PNN Learner (DDA)1 %
- RProp MLP Learner1 %
- Logistic Regression Predictor1 %
- Many to One (PMML)1 %
- Missing Value1 %
Column Rename1 %CASE Switch Variable (Start)1 %- Category to Class1 %
- Random Forest Predictor1 %
- Normalizer1 %
- Cell to Model< 1 %
- Math Formula< 1 %
CSV Reader< 1 %File Reader< 1 %- X-Aggregator< 1 %
- SVM Learner< 1 %
- SVM Predictor< 1 %
- Gradient Boosted Trees to PMML< 1 %
- Cross Joiner< 1 %
- Reference Column Filter< 1 %
- Row Splitter< 1 %
- RowID< 1 %
- Column Expressions< 1 %
Excel Reader (XLS)< 1 %- CSV Reader< 1 %
- Model Reader< 1 %
- Naive Bayes Learner< 1 %
- PMML Model Appender< 1 %
- Number to String< 1 %
- One to Many< 1 %
- Column Filter< 1 %
- Row Filter< 1 %
- CASE Switch End< 1 %
- Excel Reader< 1 %
- Table Editor (JavaScript)< 1 %
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