Techniques Outlier Detection

We use a sample of the airline data to detect outlier airports based on the average arrival delay in them. The techniques we apply are numeric outlier, z-score, DBSCAN and isolation forest. Outliers detected by each of these techniques are visualized on a map of US using the KNIME OSM integration.

Techniques Outlier Detection

 

Resources

EXAMPLES Server: 02_ETL_Data_Manipulation/01_Filtering/07_Four_Techniques_Outlier_Detection/Four_Techniques_Outlier_Detection02_ETL_Data_Manipulation/01_Filtering/07_Four_Techniques_Outlier_Detection/Four_Techniques_Outlier_Detection*
Download a zip-archive

 

 


* Find more about the Examples Server here.
The link will open the workflow directly in KNIME Analytics Platform (requirements: Windows; KNIME Analytics Platform must be installed with the Installer version 3.2.0 or higher). In other cases, please use the link to a zip-archive or open the provided path manually

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