I am working on a binary classification model. Currently, when I use scikit logistic regression, it outputs binary values like 0s and 1s. However, I understand, from online reading, that it outputs probability, and based on threshold of 0.5, converts them into two classes.
1) Does building a risk prediction model mean just stopping our project as soon as we get the probability output and not apply this threshold? Is that what is called as Risk prediction model? If yes, how do I do that using scikit logistic regression?
2) Does scikit logistic allow us modify the threshold?
3) Can all classification algorithms like SVM, RF, XGBOOST, etc. be used to build a risk prediction model without going for the threshold cutoff?