Based on a trained MultiLayerPerceptron-model given at the model inport of this node, the expected output values are computed. If the output variable is nominal, the output of each neuron and the class of the winner neuron are produced. Otherwise, the regression value is computed. Filter out missing values before using this node.
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- Partitioning12 %
- Normalizer (Apply)5 %
- Normalizer3 %
- X-Partitioner3 %
String To Number2 %- Column Filter2 %
- Equal Size Sampling1 %
- Model Reader1 %
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Naive Bayes Learner< 1 %- Missing Value< 1 %
Number To String< 1 %- Rule-based Row Splitter< 1 %
Recursive Loop Start< 1 %- Excel Reader< 1 %
Column Rename< 1 %- Rule-based Row Filter< 1 %
PCA Apply< 1 %- Correlation Filter< 1 %
- CSV Reader< 1 %
- Expand Bit Vector< 1 %
- ARFF Reader< 1 %
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- k-Means< 1 %
Linear Correlation< 1 %- PMML Reader< 1 %
- Rank Correlation< 1 %
- PNN Learner (DDA)< 1 %
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- Scorer< 1 %
Column Appender< 1 %- Scatter Plot (JavaScript)< 1 %
Row Filter (deprecated)< 1 %- Math Formula< 1 %
- PCA Apply< 1 %
- File Reader< 1 %
PMML Reader< 1 %- Naive Bayes Predictor< 1 %
Table Reader< 1 %- SMOTE< 1 %
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- Lag Column< 1 %
- Reference Row Filter< 1 %
- ROC Curve (legacy)< 1 %
Excel Reader (XLS)< 1 %- Simple Regression Tree to PMML< 1 %
- X-Aggregator< 1 %
- Hierarchical Clustering< 1 %
Regression Predictor< 1 %- SVM Learner< 1 %
- Category to Number< 1 %
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Color Appender< 1 %- Number to String< 1 %
- Linear Correlation< 1 %
- Domain Calculator< 1 %
- Duplicate Row Filter< 1 %
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Naive Bayes Predictor< 1 %- Cluster Assigner< 1 %
- MultiLayerPerceptron Predictor< 1 %
PCA< 1 %- Logistic Regression Learner< 1 %
Scorer< 1 %- Category to Number (Apply)< 1 %
- Reference Column Filter< 1 %
Row Splitter (deprecated)< 1 %- Missing Value (Apply)< 1 %
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- Statistics< 1 %
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- Cell to PMML< 1 %
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XLS Reader< 1 %- Regression Predictor< 1 %
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- Number Rounder< 1 %
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- Column Auto Type Cast< 1 %
- Table to PMML Ensemble< 1 %
Counting Loop Start< 1 %- PNN Predictor< 1 %
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Logistic Regression Learner< 1 %- Bootstrap Sampling< 1 %
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- Normalizer (PMML)< 1 %
- Polynomial Regression Learner< 1 %
- String to Number< 1 %
- Denormalizer (PMML)< 1 %
- DB Reader< 1 %
- Cell to Model< 1 %
Excel Reader (XLS)< 1 %Read Excel Sheet Names (XLS)< 1 %- Parameter Optimization Loop Start< 1 %
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File Reader< 1 %- Logistic Regression Predictor< 1 %
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Python Script (1⇒1)< 1 %- RowID< 1 %
- Decision Tree to Ruleset< 1 %
- One to Many (PMML)< 1 %
CSV Reader< 1 %- Java Snippet< 1 %
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Loop End< 1 %- Constant Value Column< 1 %
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String To Number (PMML)< 1 %- Rule Engine< 1 %
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- R Snippet< 1 %
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Table Row To Variable Loop Start< 1 %- Numeric Binner< 1 %
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K Nearest Neighbor (Distance Function)< 1 %Excel Reader (XLS)< 1 %- GET Request< 1 %
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Line Reader< 1 %- Fuzzy Rule Learner< 1 %
K Nearest Neighbor< 1 %- MDS< 1 %
PCA Inversion< 1 %- SVM Predictor< 1 %
- Number to Category (Apply)< 1 %
- Many to One< 1 %
- Nominal Value Row Filter< 1 %
- Sorter< 1 %
- Value Counter< 1 %
- Cronbach Alpha< 1 %
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- Crosstab< 1 %
- H2O to Table< 1 %
- Double Input (legacy)< 1 %
- Python Source (legacy)< 1 %
Database Looping< 1 %- Recursive Loop Start< 1 %
- SOTA Learner< 1 %
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- Timer Info< 1 %
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Table Column to Variable< 1 %Database Connection Table Reader< 1 %Database Reader< 1 %PMML Reader< 1 %Model Reader< 1 %- Tree Ensemble Predictor< 1 %
Random Forest Learner< 1 %Concatenate (Optional in)< 1 %- Auto-Binner< 1 %
- Cross Joiner< 1 %
- Table Validator (Reference)< 1 %
- HiLite Row Splitter< 1 %
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Joiner< 1 %- Row Sampling< 1 %
- String Manipulation< 1 %
- Target Shuffling< 1 %
- Table Transposer< 1 %
- Box Plot (legacy)< 1 %
DL Network Executor< 1 %- PMML to Cell< 1 %
- Index Query< 1 %
- Java Snippet Row Splitter< 1 %
Document Vector Adapter< 1 %- JSON to Table< 1 %
- Window Loop Start< 1 %
- Combine Columns by Header< 1 %
- URI Port to Variable< 1 %
- Image to Table< 1 %
- Read Images< 1 %
SQL Extract< 1 %Database Numeric-Binner< 1 %Database Table Selector< 1 %- Extract System Properties< 1 %
List Files< 1 %Model Writer< 1 %Backward Feature Elimination Filter< 1 %- Feature Selection Loop Start (1:1)< 1 %
- Chunk Loop Start< 1 %
- Column List Loop Start< 1 %
- Group Loop Start< 1 %
- K Nearest Neighbor< 1 %
- MDS (DistMatrix)< 1 %
- Entropy Scorer< 1 %
- Gradient Boosted Trees Predictor< 1 %
- Random Forest Learner (Regression)< 1 %
- PMML Simple Regression Tree Predictor< 1 %
- PMML Model Appender< 1 %
Cell Replacer< 1 %- Cell Splitter< 1 %
- Column Combiner< 1 %
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- Column Rename (Regex)< 1 %
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- Pivot< 1 %
- Numeric Binner (PMML)< 1 %
- Number to String (PMML)< 1 %
- String Replacer< 1 %
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CASE Switch Model (Start)< 1 %- IF Switch< 1 %
- Extract Table Dimension< 1 %
- Data Generator< 1 %
- Conditional Box Plot (legacy)< 1 %
- HiLite Table (legacy)< 1 %
- PMML Transformation Apply< 1 %
- SDF Extractor< 1 %
- Random Item Inserter< 1 %
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Read XLS Sheet Names< 1 %- Radar Plot Appender< 1 %
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- Word Vector Apply (legacy)< 1 %
- Topic Extractor (Parallel LDA)< 1 %
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- File Chooser (legacy)< 1 %
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- Image Normalizer< 1 %
MongoDB Reader< 1 %Python Source< 1 %Python Script (2⇒1)< 1 %- POST Request< 1 %
- Date/Time Shift (legacy)< 1 %
- Moving Average< 1 %
XML Reader< 1 %Simple File Reader< 1 %- File Reader (Complex Format)< 1 %
- Feature Selection Loop Start (2:2)< 1 %
Generic Loop Start< 1 %- Random Forest Predictor (Regression)< 1 %
- Edit Numeric Domain< 1 %
- Column Filter (PMML)< 1 %
- Capture Workflow Start< 1 %
- Multiple Selection Widget< 1 %
- Python Script (legacy)< 1 %
- String to Date&Time< 1 %
- Molecular Properties< 1 %
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