Hello everyone newbie data scientist here.
I'm working on a project to predict companies (probability of default) bankruptcy probability and to assign them a credit rating/score based on that :
For example below 50 probability is good and above is bad ( just for the example)
I have a dataset contains financial ratios and a class refers if the company is bankrupted or not (0 and one).
I'm planning to use this models:
Logistic regression linear discrimination analysis, decision trees, random forest, ANN, adaboost, Svm.
The question is and i know it is a dumb question:
Does those models return a probability? Which i can transform to labels, I saw that in a thesis and I'm not sure about it.
Otherwise, any guidance,tips anything will be appreciated.
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