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Decision Analytic Thinking: What is a Good Model? (Chapter 7) (Expected…
Decision Analytic Thinking: What is a Good Model? (Chapter 7)
The Confusion Matrix
Class confusion
Contingency table
n*n matrix
Actual Classes
Predicted Classes
False positives
False Negatives
Expected Value
Structure of problem
Elements of the analysis extracted from data
Elements of analysis that need to be acquired from other sources
Decision outcomes
Probability
Value
Mining (induction)
Use of a model
Using expected value
Likely responder
Not likely responder
"Common sense" threshold
Decision Rule
Profit
Aggregate
Predicted to churn
Actually does not churn
Cost-Benefit Matrix
Rows and columns
Predicted (Y N)
Actual (p and n)
Can't be estimated
Depend on external information
Require analysis
True positive
True negative
False positive
False negative
Evaluation, Baseline Performance, and Implications for investments in data
Reasonable baseline
Model Performance
Majority classifer
Conditional Model performance
Data sources
Commitments of personal time
Actual costs (monetary)