Miasm1 Registered Posts: 7 ✭

August 2023 in General Discussion

Hi all,

How do you handle missing values and outliers in Dataiku? Any plugins or workflows you'd recommend for efficient data cleaning?

Thanks for your tips!

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Answers

• 

  Alexandru Dataiker, Dataiku DSS Core Designer, Dataiku DSS ML Practitioner, Dataiku DSS Adv Designer, Registered Posts: 1,269 Dataiker

  August 2023

  Hi @Miasm1
  ,

  1) For missing values -> https://doc.dataiku.com/dss/latest/machine-learning/features-handling/index.html#features-handling you can handle as part of feature handling.
  https://knowledge.dataiku.com/latest/ml-analytics/model-design/concept-feature-handling.html#handle-missing-values
  
  2) For outlier on clustering models see : https://doc.dataiku.com/dss/latest/machine-learning/unsupervised/settings.html#outliers-detection
  
  You can use code -> https://developer.dataiku.com/latest/tutorials/plugins/recipes-clipping-dataset/index.html

  Or prepare recipe
  https://doc.dataiku.com/dss/latest/preparation/processors/number-clipping.html
  
  
  
  

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  Turribeach Dataiku DSS Core Designer, Neuron, Dataiku DSS Adv Designer, Registered, Neuron 2023 Posts: 2,384 Neuron

  August 2023

  @AlexT
  It's a bot.

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