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The precision of your cascade classifier is determined by your Acceptance Ratio of the last stage. Technically, the acceptance ratio break value tells how much your model should continue to learn and when to stop.It must ideally be around 0.0000412 or so.
If it is 4.8789e-05, it signifies that your cascade is overtrained and will not detect the objects. In this case, you will have to reduce the number of stages you set and increase the number of learning samples( give in more negative and positive images)
