Assignment 8
Ela Montopoli and Alex Scaramuzzino
2024-04-11
Objective
Predict attrition using the CreditCard data from the AER
package, using the classification algorithm from the rpart
package.
Data Prep
- Created a new binary variable
attritionby classifying observations with an Attritioned User as0, and with an Existing customer as1. - Split the data (10127 observations), into training and validation datasets (70%/30% , 7137/2990)
The Tree
Two Interpretations from the Tree
- The most likely attritioned customers:
- have a relationship count < 3
- Smaller rolving balance (relovling balance < 614)
- Less transactions (total transactions < 79)
- Unlikely attrition
- Heavy User (total transactions >= 5423)
Variable Importance
Interesting how balance is perceived by many as a predictor for attrition. However, the data shows that it is not a good predictor
Model Accuracy
Using the validation data, it is observed that the model is able to:
- Predict correctly 100% of attrition
- Misclassify existing customers as attritioned 0% of the time
##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 2990
##
##
## | validation_tree$atrittion_predicted
## validation_tree$atrittion_predicted | Attrited Customer | Existing Customer | Row Total |
## ------------------------------------|-------------------|-------------------|-------------------|
## Attrited Customer | 454 | 0 | 454 |
## | 2150.935 | 385.065 | |
## | 1.000 | 0.000 | 0.152 |
## | 1.000 | 0.000 | |
## | 0.152 | 0.000 | |
## ------------------------------------|-------------------|-------------------|-------------------|
## Existing Customer | 0 | 2536 | 2536 |
## | 385.065 | 68.935 | |
## | 0.000 | 1.000 | 0.848 |
## | 0.000 | 1.000 | |
## | 0.000 | 0.848 | |
## ------------------------------------|-------------------|-------------------|-------------------|
## Column Total | 454 | 2536 | 2990 |
## | 0.152 | 0.848 | |
## ------------------------------------|-------------------|-------------------|-------------------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 2990 d.f. = 1 p = 0
##
## Pearson's Chi-squared test with Yates' continuity correction
## ------------------------------------------------------------
## Chi^2 = 2982.24 d.f. = 1 p = 0
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