This node must be the end of a cross validation loop and must follow a X-Partitioner node. It collects the result from a predictor node, compares predicted class and real class and outputs the predictions for all rows and the iteration statistics.
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Popular Predecessors
Random Forest Predictor11 %Gradient Boosted Trees Predictor7 %Regression Predictor6 %- Random Forest Predictor5 %
Gradient Boosted Trees Predictor5 %- Decision Tree Predictor4 %
Tree Ensemble Predictor4 %- Regression Predictor3 %
- SVM Predictor3 %
- MultiLayerPerceptron Predictor3 %
- K Nearest Neighbor3 %
- Logistic Regression Predictor3 %
- Naive Bayes Predictor3 %
Random Forest Predictor2 %- Gradient Boosted Trees Predictor2 %
- Random Forest Predictor (Regression)2 %
K Nearest Neighbor (Distance Function)1 %- Simple Regression Tree Predictor1 %
- Weka Predictor (3.7)1 %
Numeric Scorer1 %- Scorer1 %
- Gradient Boosted Trees Predictor (Regression)1 %
- XGBoost Predictor1 %
Random Forest Predictor (Regression)< 1 %Tree Ensemble Predictor< 1 %- X-Partitioner< 1 %
- Tree Ensemble Predictor< 1 %
- XGBoost Predictor (Regression)< 1 %
Naive Bayes Learner< 1 %- PNN Predictor< 1 %
Simple Regression Tree Predictor< 1 %PMML Predictor< 1 %- Java Snippet< 1 %
- Tree Ensemble Predictor (Regression)< 1 %
Random Forest Learner< 1 %Tree Ensemble Predictor (Regression)< 1 %- Numeric Scorer< 1 %
String To Number< 1 %Column Appender< 1 %- Denormalizer< 1 %
- K Nearest Neighbor (Distance Function)< 1 %
CSV Reader< 1 %File Reader< 1 %Concatenate (Optional in)< 1 %- GroupBy< 1 %
Excel Reader (XLS)< 1 %- Logistic Regression Learner< 1 %
- LIBSVMPredictor< 1 %
- Text Classifier Predictor< 1 %
- Scorer (JavaScript)< 1 %
CSV Writer< 1 %Number To String< 1 %- Cross Joiner< 1 %
- Rule Engine< 1 %
- Python Script (legacy)< 1 %
Variable to Table Column< 1 %- Category to Number< 1 %
- Partitioning< 1 %
- H2O to Table< 1 %
PMML Ensemble Predictor< 1 %- Parameter Optimization Loop Start< 1 %
- Normalizer (Apply)< 1 %
- Loop End< 1 %
- Cluster Assigner< 1 %
PMML Gradient Boosted Trees Predictor< 1 %Tree Ensemble Learner< 1 %- DL4J Feedforward Predictor (Regression) (legacy)< 1 %
- H2O Numeric Scorer< 1 %
- Naive Bayes Learner< 1 %
- Column Appender< 1 %
- Excel Reader< 1 %
Loop End< 1 %Logistic Regression Learner< 1 %- SOTA Predictor< 1 %
- Concatenate< 1 %
Column Rename< 1 %- R Predictor< 1 %
- Correlation Filter< 1 %
- Keras Network Executor< 1 %
- Variable Loop End< 1 %
- Number to Category (Apply)< 1 %
- Loop End (Column Append)< 1 %
- X-Aggregator< 1 %
- Fuzzy Rule Predictor< 1 %
- k-Means< 1 %
- PMML Gradient Boosted Trees Predictor (Regression)< 1 %
- Random Forest Learner< 1 %
- Double to Integer< 1 %
Joiner< 1 %- Normalizer< 1 %
- String Manipulation< 1 %
- ROC Curve (legacy)< 1 %
- DL4J Feedforward Predictor (Classification) (legacy)< 1 %
- Math Formula< 1 %
- Parameter Optimization Loop End< 1 %
Python Script (2⇒1)< 1 %- Python Predictor (legacy)< 1 %
- Number to String< 1 %
- Linear Correlation< 1 %
- Joiner< 1 %
- Numeric Row Splitter< 1 %
- Weka Predictor (3.6) (legacy)< 1 %
Python Script (2⇒1)< 1 %- Category to Number (Apply)< 1 %
- Capture Workflow End< 1 %
- Column Expressions< 1 %
- CSV Reader< 1 %
- Create Collection Column< 1 %
Naive Bayes Predictor< 1 %- Fuzzy Rule Learner< 1 %
- PNN Learner (DDA)< 1 %
- Linear Regression Learner< 1 %
- PMML Simple Regression Tree Predictor< 1 %
- Column Aggregator< 1 %
Double To Int< 1 %- Equal Size Sampling< 1 %
- Column Filter< 1 %
Row Filter (deprecated)< 1 %- Missing Value< 1 %
- RowID< 1 %
- Lift Chart (legacy)< 1 %
- Color Manager< 1 %
- Fingerprint Bayesian Predictor< 1 %
DL Network Executor< 1 %- Java Snippet (simple)< 1 %
- Weka Cluster Assigner (3.7)< 1 %
- Decision Tree View (JavaScript)< 1 %
- Chunk Loop Start< 1 %
- Hierarchical Cluster Assigner (local)< 1 %
- Association Rule Learner< 1 %
- PMML Gradient Boosted Trees Predictor< 1 %
- Random Forest Learner (Regression)< 1 %
- String to Number< 1 %
- Duplicate Row Filter< 1 %
- Linear Discriminant Analysis Apply< 1 %
- PMML Predictor< 1 %
- CSV Writer< 1 %
- Linear Discriminant Analysis< 1 %
- ROC Curve (JavaScript)< 1 %
- Conformal Classification< 1 %
- SVM Learner< 1 %
- Workflow Executor< 1 %
- Scatter Plot (JavaScript)< 1 %
- Silhouette Coefficient< 1 %
- Column Merger< 1 %
- Column Rename (Regex)< 1 %
- String Splitter (Regex)< 1 %
- String Replacer< 1 %
- Table Transposer< 1 %
- Rule-based Row Filter< 1 %
- Java Edit Variable< 1 %
- Polynomial Regression Learner< 1 %
- Numeric Binner< 1 %
- Crosstab< 1 %
- Variable to Table Column< 1 %
- Model Writer< 1 %
- Table Row to Variable Loop Start< 1 %
Table Reader< 1 %Random Forest Learner< 1 %Cell Replacer< 1 %- JPMML Regression Predictor< 1 %
- Extract Variables (Data)< 1 %
Table Row to Variable< 1 %- Feature Selection Loop End< 1 %
- Group Loop Start< 1 %
- MDS Projection< 1 %
PCA Apply< 1 %- Entropy Scorer< 1 %
- SMOTE< 1 %
- PCA< 1 %
- Auto-Binner< 1 %
- Table Validator< 1 %
- Filter Apply< 1 %
- DL Python Network Executor< 1 %
- PMML Ensemble Predictor< 1 %
- Column Filter (legacy)< 1 %
- R Snippet< 1 %
- Conformal Prediction Loop End< 1 %
- Hierarchical Clustering< 1 %
- DB Writer< 1 %
- k-Medoids< 1 %
XGBoost Linear Ensemble Learner (Regression)< 1 %XGBoost Tree Ensemble Learner< 1 %- ARIMA Predictor< 1 %
Database Reader< 1 %K Nearest Neighbor< 1 %Scorer< 1 %Random Forest Learner (Regression)< 1 %Cell Splitter< 1 %- Column Comparator< 1 %
- Row Sampling< 1 %
Excel Reader (XLS)< 1 %- Domain - Similarity< 1 %
Table Row to Variable< 1 %Model Writer< 1 %- DBSCAN< 1 %
- Decision Tree Learner< 1 %
PMML Gradient Boosted Trees Predictor< 1 %- Edit Numeric Domain< 1 %
- Denormalizer (PMML)< 1 %
- Normalizer (PMML)< 1 %
- Column Splitter< 1 %
Rank Correlation< 1 %- Statistics< 1 %
- Spark to Table< 1 %
- Boosting Predictor Loop End< 1 %
- Voting Loop End< 1 %
- NG Predictor (beta)< 1 %
Python Script (1⇒1)< 1 %- Table Row to Variable< 1 %
- Decision Tree to Ruleset< 1 %
- H2O Binomial Scorer< 1 %
- Fingerprint Clustering< 1 %
- Feature Selection Filter< 1 %
k-Means< 1 %- Tree Ensemble Learner< 1 %
- Constant Value Column< 1 %
- Reference Column Filter< 1 %
- Missing Value Column Filter< 1 %
- Number Rounder< 1 %
- Sorter< 1 %
- Value Counter< 1 %
- Ruleset Predictor< 1 %
- One-way ANOVA< 1 %
- Cache< 1 %
- Shape Manager< 1 %
- Boosting Learner Loop End< 1 %
- Prediction Fusion< 1 %
Python Predictor< 1 %Python Predictor< 1 %- Duplicate Filter< 1 %
- Model Acceptability Criteria< 1 %
- KNFST Novelty Scorer< 1 %
- Breakpoint< 1 %
- Catch Errors (Data Ports)< 1 %
Table Column to Variable< 1 %Variable to Table Row< 1 %- Image to Table< 1 %
- Table Creator< 1 %
Backward Feature Elimination Filter< 1 %Backward Feature Elimination End< 1 %- Feature Selection Loop Start (1:1)< 1 %
Loop End (2 ports)< 1 %Variable Condition Loop End< 1 %- Fuzzy c-Means< 1 %
PCA Inversion< 1 %- PCA Apply< 1 %
- Tree Ensemble Learner (Regression)< 1 %
- Tree Ensemble Model Extract< 1 %
- Binner (Dictionary)< 1 %
- Column Auto Type Cast< 1 %
- Column Resorter< 1 %
- Many to One< 1 %
- One to Many< 1 %
- Table Validator (Reference)< 1 %
- CAIM Applier< 1 %
- Extract Missing Value Cause< 1 %
- Constant Value Column Filter< 1 %
Row Splitter (deprecated)< 1 %- Pivot< 1 %
- Missing Value (Apply)< 1 %
- Number to String (PMML)< 1 %
- String Manipulation (Variable)< 1 %
- Numeric Outliers< 1 %
- Single sample t-test< 1 %
CASE Switch Data (End)< 1 %- Timer Info< 1 %
- Conditional Box Plot (legacy)< 1 %
- Spark Scorer< 1 %
- Parallel Chunk End< 1 %
- TimeDelay Loop End< 1 %
- Model Loop End< 1 %
- DL4J Feedforward Predictor (Layer) (legacy)< 1 %
- External Tool< 1 %
- H2O MOJO Predictor (Classification)< 1 %
- H2O MOJO Predictor (Regression)< 1 %
- H2O Predictor (Classification)< 1 %
- Association Rule Learner (Borgelt)< 1 %
- Math Formula (Multi Column)< 1 %
- Math Formula (Variable)< 1 %
XLS Reader< 1 %Excel Reader (XLS)< 1 %- Vocabulary Extractor (legacy)< 1 %
- PDF Parser< 1 %
- Column Selection Configuration< 1 %
- Integer Widget< 1 %
Python Script (1⇒1)< 1 %Python Script (2⇒2)< 1 %- R to Table< 1 %
- Date Field Extractor (legacy)< 1 %
- Moving Aggregator< 1 %
RMSE Calculator< 1 %- Append to Collection< 1 %
- File Reader< 1 %
- Table Reader< 1 %
- Tree Ensemble Statistics< 1 %
- Reference Column Splitter< 1 %
- String to Number (PMML)< 1 %
- Independent groups t-test< 1 %
- Fingerprint Bayesian Learner< 1 %
- DB Delete (Table)< 1 %
- Similarity Search< 1 %
- H2O Multinomial Scorer< 1 %
- StanfordNLP NE Scorer< 1 %
- Binary Classification Inspector< 1 %
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