Intercept

In data science, intercept refers to the value at which the regression line crosses the y-axis. It is the value of the dependent variable when all independent variables are equal to zero. Intercept is an important parameter in linear regression models as it helps to determine the starting point of the regression line. It is also used to calculate the predicted value of the dependent variable when the independent variable is zero. The intercept can be positive, negative or zero depending on the data and the model. In logistic regression, the intercept is the log odds of the dependent variable when all independent variables are equal to zero.
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