This is one of my model variants. It achieves an AUC score of 0.73. Another one of my model variants achieves an AUC score of 0.7265. Below is the the confusion matrix -
Like many problems, the minority class(positive class) is what is important for merepresents the customers I'd like to target. But having many false positives is going to cost me money.
Q - how to select a model and how such a massive difference in confusion matrix gives similar AUC scores?
This is one of my model variants. It achieves an AUC score of 0.73. Another one of my model variants achieves an AUC score of 0.7265. Below is the the confusion matrix -
Like many problems, the minority class(positive class) is what is important for me. But having many false positives is going to cost me money.
Q - how to select a model and how such a massive difference in confusion matrix gives similar AUC scores?
This is one of my model variants. It achieves an AUC score of 0.73. Another one of my model variants achieves an AUC score of 0.7265. Below is the the confusion matrix -
Like many problems, the minority class(positive class) represents the customers I'd like to target. But having many false positives is going to cost me money.
Q - how to select a model and how such a massive difference in confusion matrix gives similar AUC scores?
This is one of my model variants. It achieves an AUC score of 0.73. Another one of my model variants achieves an AUC score of 0.7265. Below is the the confusion matrix -
Like many problems, the minority class(positive class) is what is important for me. But having many false positives is going to cost me money.
Q - how to select a model and how such a massive difference in confusion matrix gives similar AUC scores?
