Logistic regression predicts a discrete class probability based on a continuous input. The model below is based on the Anglican implementation of logistic regression.

```
(define xs '(-10 -5 2 6 10))
(define labels '(#f #f #t #t #t))
(define samples
(mh-query
1000 10
(define m (gaussian 0 1))
(define b (gaussian 0 1))
(define sigma-squared (gamma 1 1))
(define (y x)
(gaussian (+ (* m x) b) sigma-squared))
(define (sigmoid x)
(/ 1 (+ 1 (exp (* -1 (y x))))))
(sigmoid 8)
(all
(map (lambda (x label) (equal? (flip (sigmoid x) label) label))
xs
labels))))
(density samples "P(label=#t) for x=8" #t)
```

References: