This node defines the loop end in a sequence of models that are applied to a test dataset. In each iteration the selected prediction column is stored and the most frequent value is determined from this collection of prediction columns. A new column with the name of the selected column containing the majority class of all predictions is appended to the output table. The selected prediction columns are appended (depending on 'Remove individual prediction' option) to the resulting table; all other columns are not part of the output table.
Options
Popular Predecessors
- Decision Tree Predictor10 %
Scorer5 %- Prediction Fusion4 %
Random Forest Predictor4 %Naive Bayes Predictor3 %Regression Predictor3 %- Simple Regression Tree Predictor3 %
- Model Loop End3 %
- Excel Writer3 %
- SVM Predictor3 %
- Scorer3 %
Gradient Boosted Trees Predictor2 %Joiner2 %- Naive Bayes Predictor2 %
- PMML Gradient Boosted Trees Predictor2 %
Random Forest Predictor2 %CSV Writer2 %- Parameter Optimization Loop End2 %
Loop End2 %- Logistic Regression Predictor2 %
- Random Forest Predictor (Regression)2 %
- Weka Predictor (3.7)2 %
- Regression Predictor2 %
- Gradient Boosted Trees Predictor2 %
- Gradient Boosted Trees Predictor (Regression)2 %
- Random Forest Predictor2 %
- Joiner2 %
- ROC Curve (legacy)1 %
- XGBoost Predictor (Regression)1 %
- Variable Loop End1 %
- Tree Ensemble Predictor (Regression)1 %
- X-Aggregator1 %
- Fuzzy Rule Predictor1 %
Tree Ensemble Predictor1 %File Reader1 %- XGBoost Predictor1 %
- MultiLayerPerceptron Predictor< 1 %
Tree Ensemble Predictor (Regression)< 1 %Random Forest Predictor (Regression)< 1 %Number To String< 1 %PMML Ensemble Predictor< 1 %- Inject Variables (Data)< 1 %
Tree Ensemble Learner< 1 %- PDF Parser< 1 %
Table Writer< 1 %- Feature Selection Loop End< 1 %
Loop End (2 ports)< 1 %- PNN Predictor< 1 %
K Nearest Neighbor< 1 %- Entropy Scorer< 1 %
Gradient Boosted Trees Predictor< 1 %- Tree Ensemble Predictor< 1 %
- Concatenate< 1 %
Column Appender< 1 %- Linear Correlation< 1 %
Row Filter (deprecated)< 1 %- RowID< 1 %
- Rule-based Row Filter< 1 %
- Decision Tree to Ruleset< 1 %
- Boosting Learner Loop End< 1 %
- Boosting Learner Loop Start< 1 %
- Model to Cell< 1 %
PMML Predictor< 1 %- H2O to Table< 1 %
Excel Reader (XLS)< 1 %- JPMML Regression Predictor< 1 %
Counting Loop Start< 1 %- Chunk Loop Start< 1 %
- Group Loop Start< 1 %
- Reference Row Filter< 1 %
- PMML Ensemble Predictor< 1 %
- DL4J Feedforward Predictor (Classification) (legacy)< 1 %
- ROC Curve (JavaScript)< 1 %
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