Logistic regression is a regression model for a binary response in which the logit function of the conditional probability 
of success is a linear function
of the explanatory variables,
or equivalently 
is the sigmoid function evaluated at the linear
predictor. The coefficients are usually estimated by maximum
likelihood.
See also
Maximum Likelihood,
Regression,
Sigmoid Function
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References
Agresti, A. Categorical
Data Analysis. New York: Wiley, pp. 115-117, 1990.
Cite this as:
Weisstein, Eric W. "Logistic Regression."
From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/LogisticRegression.html
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