December 29, 2020
Logistic regression, though named regression, is a classification algorithm. It is most appropriate for binary classification problems. Here instead of predicting the actual value of the target variable, we predict the probability of the target variable falling in either class. Since the predicted value, i.e. probability, is a continuous term hence the term regression in its name is justified.
Like linear regression, in logistic regression too we try to find the slope and intercept of a line. But here instead of finding a line that is closes to the data points we find a line that divides the points belonging to once class from the other class in a manner that it covers most data points and is farthest from the data points of either class.
by : Monis Khan
Quick Summary:
Logistic regression, though named regression, is a classification algorithm. It is most appropriate for binary classification problems. Here instead of predicting the actual value of the target variable, we predict the probability of the target variable falling in either class. Since the predicted value, i.e. probability, is a continuous term hence the term regression in […]