Applies a regression XGBoost model to predict data.
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Popular Predecessors
- XGBoost Tree Ensemble Learner (Regression)18 %
- XGBoost Linear Model Learner (Regression)17 %
- Partitioning3 %
XGBoost Linear Ensemble Learner (Regression)3 %XGBoost Tree Ensemble Learner (Regression)3 %- X-Partitioner2 %
- Reference Row Filter2 %
Column Rename2 %- Math Formula (Multi Column)2 %
- XGBoost Tree Ensemble Learner2 %
CSV Reader1 %Row Splitter (deprecated)1 %- CSV Reader1 %
- XGBoost Linear Model Learner1 %
- Category to Number (Apply)1 %
- XGBoost Predictor1 %
- Lag Column1 %
- Group Loop Start1 %
- Rule-based Row Filter< 1 %
Excel Reader (XLS)< 1 %- Model Reader< 1 %
- Missing Value< 1 %
- Row Sampling< 1 %
- Sorter< 1 %
- Column Splitter< 1 %
- Rule-based Row Splitter< 1 %
- Capture Workflow Start< 1 %
- Concatenate< 1 %
- Math Formula< 1 %
- Chunk Loop Start< 1 %
Recursive Loop Start< 1 %- Random Forest Predictor (Regression)< 1 %
- Constant Value Column< 1 %
- Double to Integer< 1 %
- Column Filter< 1 %
- Reference Column Filter< 1 %
Row Filter (deprecated)< 1 %- Normalizer (Apply)< 1 %
- Normalizer< 1 %
- SHAP Loop Start< 1 %
- Shapley Values Loop Start< 1 %
XGBoost Linear Ensemble Learner< 1 %XGBoost Tree Ensemble Learner< 1 %- Feature Selection Loop Start (1:1)< 1 %
- Column Resorter< 1 %
- Joiner< 1 %
- Excel Reader< 1 %
- Excel Writer< 1 %
- Table Reader< 1 %
- RDKit Descriptor Calculation< 1 %
- CASE Switch Start< 1 %
- Parameter Optimization Loop Start< 1 %
Number To String< 1 %- Cell to Model< 1 %
- Gradient Boosted Trees Predictor (Regression)< 1 %
- Number to String< 1 %
- One to Many< 1 %
- R Snippet< 1 %
- Date&Time Part Extractor< 1 %
- GroupBy< 1 %
- Table Creator< 1 %
- SMOTE< 1 %
- Column Appender< 1 %
Model Reader< 1 %Variable to Table Column< 1 %Variable to Table Row< 1 %File Reader< 1 %- Regression Predictor< 1 %
- Expand Bit Vector< 1 %
- Domain Calculator< 1 %
- Reference Row Splitter< 1 %
Joiner< 1 %- Normalizer Apply (PMML)< 1 %
- Shuffle< 1 %
- Numeric Outliers (Apply)< 1 %
- DB Query Reader< 1 %
- Model Loop Start< 1 %
- Date&Time-based Row Filter< 1 %
- Date Field Extractor (legacy)< 1 %
- Recursive Loop Start< 1 %
- Reference Column Splitter< 1 %
- PMML Transformation Apply< 1 %
- Parallel Chunk End< 1 %
- Boosting Predictor Loop Start< 1 %
- XGBoost Predictor (Regression)< 1 %
- Integer Input (legacy)< 1 %
- Fingerprints Expander< 1 %
- Create Collection Column< 1 %
- Catch Errors (Generic Ports)< 1 %
Table Reader< 1 %- Column List Loop Start< 1 %
- Fuzzy Rule Predictor< 1 %
- Random Forest Learner (Regression)< 1 %
- Bootstrap Sampling< 1 %
- Category to Number< 1 %
- String to Number< 1 %
- Equal Size Sampling< 1 %
- Missing Value Column Filter< 1 %
- Missing Value (Apply)< 1 %
- String to Number (PMML)< 1 %
- Number Rounder< 1 %
- Numeric Row Splitter< 1 %
- Target Shuffling< 1 %
- Keras Network Executor< 1 %
- H2O to Table< 1 %
Excel Reader (XLS)< 1 %- LIME Loop Start< 1 %
Extract Date&Time Fields< 1 %- Moving Average< 1 %
- Table Row to Variable< 1 %
- Counting Loop Start< 1 %
- Generic Loop Start< 1 %
- X-Aggregator< 1 %
- PCA< 1 %
- Auto-Binner (Apply)< 1 %
- Constant Value Column Filter< 1 %
- Normalizer (PMML)< 1 %
- Numeric Outliers< 1 %
- Column Expressions< 1 %
- Column Filter (legacy)< 1 %
- Table View (JavaScript)< 1 %
Python Script (2⇒1)< 1 %- Window Loop Start< 1 %
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Workflows
02_AutoML_Regression_and_Classification_ExamplesKNIME Hub- 02_AutoML_Regression_and_Classification_ExamplesKNIME Hub
- 02_Housing_Value_Regression_with_XGBoostKNIME Hub
- 02_Housing_Value_Regression_with_XGBoostKNIME Hub
- 02_SHAP_and_Shapley_ValuesKNIME Hub
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