Libraries to get calibrated probabilities for ML outlier detection algorithm ?

I am currently developping a 2 class classification algorithm. However, as the dataset is at the moment really small (<50 observations) and imbalanced (~1/10 ratio), I decided to rather first concentrate on developing a one class, i.e. outlier detection ML algorithm. Moreover, I'll need to get from this ML algorithm, an estimate of the conditional probability P(Outlier|X). As I have read that conditional probabilites for strong imbalanced dataset, needs correct calibration, and that Platt scaling is not recommended in that case, I'd like to ask to the community here if it exist some libraries in R, Python, ... that would facilitate this calibration exercise.