CausalNex in Action — Finding the WHY Behind the Scenes

  • “What is the cause for people to churn?”
  • “If we improve this feature, how much will the churn be reduced?”

Dataset Exploration

Learning Structure from Data

Bayesian Network

  • uniform (specify the number of buckets and discretizer will create uniformly spaced buckets)
  • quantile (specify the number of buckets and discretizer will create buckets with equal percentiles)
  • outlier (specify percentile of outlier and dicretizer will create 3 buckets
  • fixed (splitting points are specified manually)

Inference

  • What would be the Outcome if all people actually had healthy weight? — If all people were with healthy weight, there will be less positive diagnosis.(from 0.42 to 0.30)
  • What would be the Outcome if all people had only a slight risk of diabetes in the family? — If all people had slight risk of diabetes in the family(based on the column DiabetesPedigreeFunction), there will be less positive diagnosis.(from 0.42 to 0.41)

Logistic Regression Comparison

Conclusion

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