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Guided_​Automation_​of_​Machine_​Learning_​Example

Guided Machine Learning

This application takes a tabular input data and creates a classification model by guiding through feature selection, outlier detection, missing value handling and model selection and fully automating feature engineering and model optimization. It automatically creates a workflow that can be deployed and used for predictions.

Modeling. Deployment. Data preparation. Configuration. 1st iteration2nd iteration Guided MissingValue Handling Guided StatisticalFeature Selection Workflow Combiner Workflow Combiner Automated FeatureGeneration Workflow Writer Automated ModelOptimization Workflow Combiner Automated FeatureSelection Workflow Combiner Guided OutlierDetection Automated MissingValue Handling Guided MissingValue Handling Guided ModelSelection Target Selection Dataset Selection Modeling. Deployment. Data preparation. Configuration. 1st iteration2nd iteration Guided MissingValue Handling Guided StatisticalFeature Selection Workflow Combiner Workflow Combiner Automated FeatureGeneration Workflow Writer Automated ModelOptimization Workflow Combiner Automated FeatureSelection Workflow Combiner Guided OutlierDetection Automated MissingValue Handling Guided MissingValue Handling Guided ModelSelection Target Selection Dataset Selection

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Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: simon
Created at: 2020-10-04
On NodePit since: 2020-12-07
Last update: 2026-01-19
Created with KNIME version: v4.2.2

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