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Mar 19th, 2018
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  1. fullmod = glm(Response ~ page_views_90d+win_visits+osx_visits+mc_1+mc_2+mc_3+mc_4+mc_5+mc_6+store_page+orders+orderlines+bookings+purchase, data=training, family=binomial)
  2. summary(fullmod)
  3. fullmod.results <- predict(fullmod, newdata = testing, type='response')
  4. plotLift(fitted.results, test_data_full$class, cumulative = TRUE,col="orange", n.buckets = 5)
  5.  
  6. redmod1 = glm(Response ~ win_visits+osx_visits+mc_2+mc_4+mc_6+store_page+orders+orderlines+bookings+purchase, data=training, family=binomial)
  7. redmod1.results <- predict(redmod1, newdata = testing, type = 'response')
  8. plotLift(redmod1.results, test_data_full$class, cumulative = TRUE,col="orange", n.buckets = 5)
  9.  
  10. # Attempt to plot multiple classifiers
  11. plotLift((redmod1.results, fullmod.results), test_data_full$class, cumulative = TRUE,col="orange", n.buckets = 5)
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