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Fully_​Automated_​Machine_​Learning_​Example

Fully Automated Machine Learning

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

Configuration. Data preparation. Modeling. Deployment. Automated MissingValue Handling Automated StatisticalFeature Selection Automated FeatureGeneration Automated ModelStacking Automated OutlierDetection Workflow Combiner Workflow Writer Workflow Combiner Workflow Combiner Workflow Combiner Automated FeatureSelection Automated ModelSelection Automated ModelOptimization Target Selection Dataset Selection Configuration. Data preparation. Modeling. Deployment. Automated MissingValue Handling Automated StatisticalFeature Selection Automated FeatureGeneration Automated ModelStacking Automated OutlierDetection Workflow Combiner Workflow Writer Workflow Combiner Workflow Combiner Workflow Combiner Automated FeatureSelection Automated ModelSelection Automated ModelOptimization 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: 2020-09-28
On NodePit since: 2020-12-07
Last update: 2026-01-21
Created with KNIME version: v4.2.2

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