Estimating conditional probabilities
A supervized learning problem - learning a mapping from input variables to
output variables - may be seen as a conditional probability estimation problem.
For instance, consider a toy example below:
||Sex (M=0, W=1)
Our training data set consists of two patients, or two examples (.
Where are features from the variables: Age and Sex, and is the
binary outcome: 1 if a patient has cancer, and 0 otherwise. Our prediction
- I want to predict the probability of cancer given data, i.e.,
My ground truth
- I can approximate this conditional probability with a
function parameterized with
Learn to approximate