center Here represents the classification threshold of your binary classifier, e.g. Likelihood Ratio.

Note When theta is high (at the bottom-left of the curve):

  • The classifier requires stronger evidence to predict the positive class
  • You get fewer false positives but also fewer true positives

As theta decreases (moving toward the top-right of the curve):

  • The classifier becomes more lenient in predicting the positive class
  • You get more true positives but also more false positives
  • This results in higher recall but lower precision

source