Logistic regression is a statistical method that predicts binary outcomes based on predictor variables. The threshold in logistic regression determines the boundary between the two categories being predicted.
Logistic regression is a statistical method used to predict the probability of a binary outcome based on predictor variables, such as predicting the likelihood of a heart attack based on factors like age and BMI.
In logistic regression, a key concept is the threshold, which refers to the value that determines the boundary between the two categories being predicted, for example, where the probability shifts from predicting one outcome to another.
Thresholds play a crucial role in logistic regression models as they define the point at which the predicted probability is considered to fall into one category or another.
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