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Outlier Detection and Handling

Demonstrates techniques for viewing summary statistics of data as well as various methods of handling numeric outliers. Also demonstrated is how to save a numeric outliers model and re-apply it later.

This example uses the "NASA Astronauts, 1959-Present" data source hosted and maintained by NASA under the CC0 1.0 Universal (CC0 1.0) Public Domain Dedication.

Outlier handling methods Summary statistics Outlier model re-use and deployment Remove non-outliersRemove outliersReplace outliersastronauts.tableSave model forlater useastronauts.tableRead model back in Statistics Numeric Outliers Numeric Outliers Numeric Outliers Numeric Outliers(Apply) Histogram Histogram Histogram Data Explorer Table Reader Model Writer Table Reader Model Reader Outlier handling methods Summary statistics Outlier model re-use and deployment Remove non-outliersRemove outliersReplace outliersastronauts.tableSave model forlater useastronauts.tableRead model back inStatistics Numeric Outliers Numeric Outliers Numeric Outliers Numeric Outliers(Apply) Histogram Histogram Histogram Data Explorer Table Reader Model Writer Table Reader Model Reader

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

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Created by: sjporter
Created at: 2021-04-30
On NodePit since: 2021-05-07
Last update: 2024-04-27
Created with KNIME version: v4.3.2
Tags: outliersnumeric outliersoutlier detection

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