The presentation focuses on the value of heuristics pre modelling and Post Modelling which can be used in solutioning or deplyment stage.

1. AI/ML
Disruptive Opportunity ?
What if Data Heuristics .. hold a Key!,
in the Last Stage of Decision Intelligence?

2. Final Output is
Segment Boundary
Technology Complexity
( # Many Class of
Classifier’s )
#Complicated Data
Transformations
Interpretability/
Expainability
AI/ML Classifier
Decision Intelligence
Complementing Heuristics
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If not Interpretability or Explainability
#Let Alone Pattern Boundaries and
Algorithm Intuitions
How else to Complement
“Understanding of Data” , while
making a Decision ?

5. Pre Process :: Extract Per Class Feature Heuristics
Post Process :: Classification, Class Specific Per Feature Heuristical Scoring, Deviations
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6. Decision Tree and Post Classifier Heuristics
• Decision Intelligence
• Heuristic Complementation – for Solution Checks
• Per Class, Per feature
• Threshold Bounds [ Min, Max ], Stats Mean/Variance,
Quartiles, No of Similar Samples etc.
• Programmable Classification Enforcement
• Application, Tolerance, Deviations, Windowing.
• Generalize for All Classifiers – Heuristic is
Data/Sample Property
• Captured and Presented for “Programmed Intelligence”
• Extend thoughts for Unsupervised
Decision TreePossible Application

7. Trending Solutioning
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Trending Solutioning

9. Two Cultures
Use Data Heuristics ( # many statistics representations )
along with ML models, towards Augmented Decision Intelligence

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Heuristic Benefiters