Adaboost prediction is the sign of the strong classifier. How can we obtain the probability of the prediction $P(y = 1 | x)$?

Can we use the logistic function or some other function as follows:

$$P(y = 1 | x) = \frac1{1+\exp(-F(x))}$$

where $F(x)$ is the strong classifier.

• Why not use gradient boosting? There is rarely a reason to use adaboost instead in 2018. – Matthew Drury Feb 17 '18 at 20:51
• Do you mean gradient boosting with exponential loss function? In that case how to convert the score into probabilities? – gnikol Feb 27 '18 at 17:02

$$F(x) = \sum_{t=1}^T \alpha_t h_t (x)$$
$$\pi(x) = \frac{1}{1+e^{-2F(x)}}$$