04_Data_Preprocessing_for_ML_Models1
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Data Preprocessing for ML Models
This workflow demonstrates the following standard preprocessing steps before training a machine learning model:
- Partitioning
- Outlier detection
- Missing value handling
- Dimensionality reduction
- Conversion
- Feature selection
URL: House Prices Dataset https://www.kaggle.com/marcopale/housing
Nodes
Extensions
- FeatureKNIME Base nodes
- FeatureKNIME Deep Learning - Keras Integration
- FeatureKNIME Ensemble Learning Wrappers
- FeatureKNIME H2O Machine Learning Integration
- FeatureKNIME Integrated Deployment
- FeatureKNIME JavaScript Views
- FeatureKNIME Javasnippet
- FeatureKNIME Math Expression (JEP)
- FeatureKNIME Optimization extension
- FeatureKNIME PMML Preprocessing Applier Nodes
- FeatureKNIME Quick Forms
- FeatureKNIME Statistics Nodes
- FeatureKNIME XGBoost Integration