For Logistic Regression using the Classification Learner App, the classifier models the class probabilities as a function of the linear combination of predictors, using the 'fitglm' function (as specified in the documentation).
The predicted response of this model to a new data set is the predicted probabilities for each class. I would like to know how does the classification learner app classifies this predicted data based on probabilities (the value for the probability at which Yes/No decisions are made).
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