This node takes columns with nominal data and maps every category to an integer. The information for the value mapping is taken from the PMML model.
This node is typically used to apply the same mapping found by a Category To Number node.
Options
Popular Successors
- Column Filter6 %
- Normalizer (Apply)5 %
- Random Forest Learner3 %
- Partitioning3 %
Number To String3 %CSV Writer3 %- Random Forest Predictor2 %
- Regression Predictor2 %
- Category to Number2 %
- Number to Category (Apply)2 %
- Row Filter1 %
- GroupBy1 %
- Missing Value1 %
- SVM Learner1 %
- Cluster Assigner1 %
Linear Correlation1 %- Normalizer1 %
- Interactive Histogram (legacy)1 %
- XGBoost Predictor (Regression)1 %
- X-Partitioner1 %
- Number to String1 %
- Linear Correlation1 %
- Keras Network Executor1 %
String To Number< 1 %- K Nearest Neighbor< 1 %
- RProp MLP Learner< 1 %
- Decision Tree Predictor< 1 %
- MultiLayerPerceptron Predictor< 1 %
- Missing Value (Apply)< 1 %
Column Rename< 1 %- Statistics< 1 %
Color Appender< 1 %- Weka Predictor (3.7)< 1 %
PMML Writer< 1 %- Logistic Regression Learner< 1 %
- Logistic Regression Predictor< 1 %
- One to Many< 1 %
- Row Splitter< 1 %
- Normalizer (PMML)< 1 %
- Histogram (legacy)< 1 %
- Interactive Table (legacy)< 1 %
- X-Aggregator< 1 %
- PCA Apply< 1 %
- Joiner< 1 %
- Numeric Outliers< 1 %
- Excel Writer< 1 %
Random Forest Predictor< 1 %- Random Forest Predictor (Regression)< 1 %
- Auto-Binner (Apply)< 1 %
- Category to Number (Apply)< 1 %
- String Manipulation< 1 %
- Line Plot (legacy)< 1 %
- Color Manager< 1 %
- Math Formula< 1 %
Regression Predictor< 1 %- Gradient Boosted Trees Predictor< 1 %
- Gradient Boosted Trees Predictor (Regression)< 1 %
- String to Number< 1 %
- Column Resorter< 1 %
- Constant Value Column Filter< 1 %
- String to Number (PMML)< 1 %
- Row Sampling< 1 %
- Sorter< 1 %
- CSV Writer< 1 %
- Model Writer< 1 %
K Nearest Neighbor< 1 %String To Number (PMML)< 1 %- Table to H2O< 1 %
PCA Apply< 1 %Cell Replacer< 1 %- Reference Column Filter< 1 %
- Table View (JavaScript)< 1 %
- Scatter Plot (JavaScript)< 1 %
- Scorer< 1 %
Scorer< 1 %- Rule Engine< 1 %
- Math Formula (Multi Column)< 1 %
- PCA< 1 %
- Random Forest Learner (Regression)< 1 %
- Column Aggregator< 1 %
Column Appender< 1 %- Rule-based Row Filter< 1 %
- Linear Discriminant Analysis< 1 %
- Numeric Distances< 1 %
- Feature Selection Loop Start (1:1)< 1 %
- Decision Tree Learner< 1 %
Tree Ensemble Predictor< 1 %- Many to One (PMML)< 1 %
- Parallel Coordinates (legacy)< 1 %
- LIBSVMPredictor< 1 %
- Category to Class< 1 %
- Date Field Extractor (legacy)< 1 %
Loop End< 1 %- Numeric Binner< 1 %
- Column Merger< 1 %
- PMML Predictor< 1 %
- Column Filter (legacy)< 1 %
- Duplicate Row Filter< 1 %
- Keras Network Learner< 1 %
- Java Snippet< 1 %
- k-Means< 1 %
- Linear Regression Learner< 1 %
- SVM Predictor< 1 %
- Tree Ensemble Predictor (Regression)< 1 %
Random Forest Learner< 1 %- Auto-Binner< 1 %
- Column Auto Type Cast< 1 %
- Correlation Filter< 1 %
- Nominal Value Row Filter< 1 %
Joiner< 1 %Normalizer< 1 %- Normalizer Apply (PMML)< 1 %
- String Replacer< 1 %
- Rule-based Row Splitter< 1 %
- Box Plot (legacy)< 1 %
- Scatter Plot (legacy)< 1 %
DL Network Executor< 1 %- R View (Table)< 1 %
- String to Date/Time (legacy)< 1 %
- Create Collection Column< 1 %
Table Writer< 1 %Backward Feature Elimination Filter< 1 %- Naive Bayes Predictor< 1 %
- PNN Learner (DDA)< 1 %
- Hierarchical Clustering< 1 %
- Hierarchical Clustering (DistMatrix)< 1 %
- Polynomial Regression Learner< 1 %
Tree Ensemble Predictor (Regression)< 1 %Random Forest Predictor< 1 %Gradient Boosted Trees Predictor< 1 %- Binner (Dictionary)< 1 %
- Create Bit Vector< 1 %
- Column Rename (Regex)< 1 %
- Domain Calculator< 1 %
- Double to Integer< 1 %
- Missing Value Column Filter< 1 %
- Reference Row Filter< 1 %
- Column Filter (PMML)< 1 %
- Denormalizer (PMML)< 1 %
- Column Splitter< 1 %
String Replace (Dictionary)< 1 %- Ruleset Editor< 1 %
Rank Correlation< 1 %- Numeric Outliers (Apply)< 1 %
- Extract Table Spec< 1 %
- ROC Curve (legacy)< 1 %
- Bar Chart (JavaScript)< 1 %
- DL4J Feedforward Learner (Regression) (legacy)< 1 %
- DL4J Feedforward Predictor (Classification) (legacy)< 1 %
Excel Writer (XLS)< 1 %- JPMML Classifier< 1 %
- Value Filter (legacy)< 1 %
- Line Plot (JavaScript)< 1 %
- Python Predictor (legacy)< 1 %
Python Script (1⇒1)< 1 %- R Learner< 1 %
Extract Date&Time Fields< 1 %XGBoost Tree Ensemble Learner< 1 %- Table Writer< 1 %
- Group Loop Start< 1 %
- Numeric Scorer< 1 %
- Concatenate< 1 %
- Column Appender< 1 %
- Column Name Extractor< 1 %
- Top k Row Filter< 1 %
- Table Transposer< 1 %
- Ruleset Predictor< 1 %
- DB Writer< 1 %
Excel Writer (XLS)< 1 %- Python Script (legacy)< 1 %
- Date&Time-based Row Filter< 1 %
Views
- This node has no views
Workflows
01_Training_a_Churn_Predictor_LogRegKNIME Hub- 04_Decision_Trees_with_PythonKNIME Hub
- Basic_Example_Adult_DatasetKNIME Hub
- BIA505_midtermProjectClassificationKNIME Forum
- Cardiovascular Disease Prediction using 'autofeat' Generated FeaturesKNIME Hub
- Show all 12 workflows
Links
- No links available
Developers
You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.