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Suppose that you have a logistic model and the predicted probabilities of a $1$ all are in $[0.2,0.3]$. So the predictions would be "0" based on a threshold of $0.5$. What would be a good threshold to choose?

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    $\begingroup$ Why would you need a treshold? $\endgroup$ – kjetil b halvorsen May 12 '18 at 15:50
  • $\begingroup$ So that I can get better predictions. Right now my model predicts all 0's. $\endgroup$ – user21478 May 12 '18 at 15:51
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    $\begingroup$ Logistic regression predicts probabilities. If these are sufficient to solve your problem, you dont need a treshold. So what are you using the regression for? $\endgroup$ – Matthew Drury May 12 '18 at 16:21
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    $\begingroup$ You will find much information here: stats.stackexchange.com/questions/127042/… $\endgroup$ – kjetil b halvorsen May 12 '18 at 16:33
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Plot the ROC curve predicting class based on the output p value, then decide visually or using an optimal threshold algorithm considering your sensitivity/specificity tolerance

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