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Mar 30th, 2017
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  1. p<-predict(gbm_model,type="response")
  2.  
  3. a FALSE TRUE
  4. FALSE 1000 238
  5. TRUE 80 410
  6.  
  7. b
  8. a FALSE TRUE
  9. FALSE 360 169
  10. TRUE 62 123
  11.  
  12. confusion(predict(gbm_model, test_sample, n.trees = 5000) > 0, test_sample$Outcome_Variable > 0)
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