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
Used extensions & nodes
Created with KNIME Analytics Platform version 4.4.2
Loading ad hoc executions
By using or downloading the workflow, you agree to our terms and conditions.
Discussions are currently not available, please try again later.