Related Questions

In a logistic regression problem an instance is similar to 60 positive instances, 20 negative instances, dissimilar to 30 positive instances, 90 negative instances. What kind of an instance is this?
The output in a logistic regression problem is yes (equivalent to 1 or true). What is its possible value?
The cost function for logistic regression and linear regression are the same.
Logistic regression is a . . . . . . . . regression technique that is used to model data having a . . . . . . . . outcome.
Generally, which of the following method(s) is used for predicting continuous dependent variable?
1. Linear Regression
2. Logistic Regression
Can a cancer detection problem be solved by logistic regression?
In a logistic regression problem, there are 300 instances. 270 people voted. 30 people did not cast their votes. What is the probability of finding a person who cast one’s vote?
Assertion (A): If regression coefficient of X on Y is greater than one, regression coefficient of Y on X must be less than one.
Reason (R): The geometric mean between two regression coefficients is the coefficient of correlation.
What is/are true about ridge regression?
1. When lambda is 0, model works like linear regression model
2. When lambda is 0, model doesn't work like linear regression model
3. When lambda goes to infinity, we get very, very small coefficients approaching
04. When lambda goes to infinity, we get very, very large coefficients approaching infinity.
Assertion (A): If regression coefficient of X on Y is greater than one, regression coefficient of Y on X must be less than one.
Reason (R): The geometric mean between two regression coefficients is the co-efficient of correlation.
On the basis of the above, choose the appropriate answer :