APPLICATION OF SUPERVISED LEARNING
SUPPORT VECTOR MACHINE SVM
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
|
|
Regression
|
|
|
correlation
|
|
|
multicollinearity
|
|
|
none of the above
|
Detailed explanation-1: -Multicollinearity occurs when independent variables in a regression model are correlated. This correlation is a problem because independent variables should be independent. If the degree of correlation between variables is high enough, it can cause problems when you fit the model and interpret the results.
Detailed explanation-2: -Multicollinearity is a situation in which the dependent variable is highly correlated with two or more of the independent variables in a multiple regression.
Detailed explanation-3: -The independent variables may also be referred to as the predictor variables or regressors. There are 3 major uses for multiple linear regression analysis. First, it might be used to identify the strength of the effect that the independent variables have on a dependent variable.
Detailed explanation-4: -The term used to describe the case when the independent variables in a multiple regression model are correlated is: causation.