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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
An artificially intelligent car knows if to brake or not based on its distance from the car in front of it. Logistic regression algorithm is used.
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?
Which of the following statements is false?  1. When value of correlation coefficient is one, the two regression lines coincide 2. The regression coefficients are independent of the change of origin and of scale 3. The sign of the regression coefficients are always the same 4. The square of the coefficient of correlation is called coefficient of determination 
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 :
Which of the following is statistical boosting based on additive logistic regression?