Hi Folks!
This is the most common type of modeling technique in which dependent variable is predicted in terms of independent variable(s). Since, this is a logistic regression model output variable should be a binary 0 or 1. However the output is in the form of probabilites varying from 0-1. This is used to predict the event such as customers churn, claim re-opening, employees attriting, etc. This is different from a linear regression model in which the output is a continuous variable such as predicting the salary of employees, cost of ticket, price of a product, etc.
This is the most common type of modeling technique in which dependent variable is predicted in terms of independent variable(s). Since, this is a logistic regression model output variable should be a binary 0 or 1. However the output is in the form of probabilites varying from 0-1. This is used to predict the event such as customers churn, claim re-opening, employees attriting, etc. This is different from a linear regression model in which the output is a continuous variable such as predicting the salary of employees, cost of ticket, price of a product, etc.
No comments:
Post a Comment