Today I have learned about Logistic Regression, it is statistical method used for analyzing dataset which has one or more independent variables that helps to determine an outcome. This type of regression has dependent variable taking 0 or 1 values. These binary values typically determine a category. Another important characteristic for logistic regression is that it can have one more than one independent variables helping to determine the output variable( dependent variable). The independent variables can also be continuous values or categorical values. Logistic Regression uses Logistic function to model the relationship between the independent variables and the probability of the binary outcome. The Logistic Function is defined as
Logit(p) = ln(p/(1-p))
Here p represents the probability of the event occurring.
Logistic Regression is widely used in wide range of areas like healthcare, finance, and social sciences. In summary we can say that Logistic Regression is tool which can be used for understanding the relationship between the independent variables and dependent variable when the outcome is categorical