Regression is used to model Interval target variables where as logistic regression is used to model Categorical varaibles.
the formula generally used: Y = m1x1+m2x2+m3x3+m4x4+c
Regression Assumptions: Input variables are linearly related to target variable and that input variables and residuals are normally distributed, and independent with a mean of 0 and constant variance.
Logistic Regression: There are no distributional requirements for inputs in Logistic regression
1 + e^-(m1x1+m2x2+m3x3+m4x4)
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