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Introduction to cart_2009

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Matthew Magistrado
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Introduction to CART Dan Steinberg Mykhaylo Golovnya [email_address] August, 2009
In The Beginning… ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Years of Struggle ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Final Triumph ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
CART ® Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Heart Disease Classification Problem
Typical CART Solution ,[object Object],[object Object],[object Object],[object Object],PATIENTS = 215 SURVIVE 178 82.8% DEAD 37 17.2% Is BP<=91? PATIENTS = 195 SURVIVE 172 88.2% DEAD 23 11.8% Is AGE<=62.5? PATIENTS = 91 SURVIVE 70 76.9% DEAD 21 23.1% Is SINUS<=.5? <= 91 > 91 <= 62.5 > 62.5 >.5 <=.5 ,[object Object],[object Object],[object Object],[object Object],Terminal Node A SURVIVE 6 30.0% DEAD 14 70.0% NODE = DEAD Terminal Node B SURVIVE 102 98.1% DEAD 2 1.9% NODE = SURVIVE Terminal Node C SURVIVE 14 50.0% DEAD 14 50.0% NODE = DEAD Terminal Node D SURVIVE 56 88.9% DEAD 7 11.1% NODE = SURVIVE
General Workflow Stage 1 Stage 2 Stage 3 Historical Data Learn Test Validate Build a Sequence of Nested Trees Monitor Performance Best Confirm Findings
Decision Questions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Tree is a Classifier ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Importance of Binary Splits ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Competitors and Surrogates ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Utility of Surrogates ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Competitors and Surrogates Are Different ,[object Object],[object Object],[object Object],[object Object],A B C A B C Split X A B C A C B Split Y ,[object Object],[object Object],[object Object]
Tree Interpretation and Use ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],CART ® - Pros and Cons
Example: Marketing Study ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Cell Phone Study: Root Node ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Optimal Model
Variable Importance and Predictive Accuracy ,[object Object],[object Object],[object Object],[object Object]
Introduction to Hot Spot Detection ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Internal Class Assignment Rule ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
General Rules ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Impact of Priors ,[object Object],[object Object],[object Object], r =0.1 ,  b =0.9  r =0.9 ,  b =0.1  r =0.5 ,  b =0.5
Varying Priors – the Key to Hot Spot Detection ,[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],Hot Spot Detection ,[object Object],[object Object]
Improving Feature Selection Process ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Constrained Trees ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Further Development of CART
References ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Introduction to cart_2009

  • 1. Introduction to CART Dan Steinberg Mykhaylo Golovnya [email_address] August, 2009
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  • 8. General Workflow Stage 1 Stage 2 Stage 3 Historical Data Learn Test Validate Build a Sequence of Nested Trees Monitor Performance Best Confirm Findings
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