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I've trained and testing a logistic regression binary-classification model using AWS Machine Learning. The evaluation has the following features:

AUC: ~95% "extremely good"

Scores/ # records graph: One large spike, basically saying that the model scores nearly all observations nearly the same, as such: ______-^-_

How would you characterize the performance of this model?

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This model is very poor at classification, despite the high AUC

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