Machine Learning - Practice Test

[#46] Suppose you have trained an SVM with linear decision boundary after training SVM, you correctly infer that your SVM model is under fitting. Which of the following is best option would you more likely to consider iterating SVM next time?

(A) you want to increase your data points

(B) you want to decrease your data points

(C) you will try to calculate more variables

(D) you will try to reduce the features

(E) you want to increase your data points

(F) you want to decrease your data points

(G) you will try to calculate more variables

(H) you will try to reduce the features

Correct Answer

(C) you will try to calculate more variables
(G) you will try to calculate more variables

[#47] How many coefficients do you need to estimate in a simple linear regression model (One independent variable)?

(A) 1

(B) 2

(C) 3

(D) 4

(E) 1

(F) 2

(G) 3

(H) 4

Correct Answer

(B) 2
(F) 2

[#48] A regression model in which more than one independent variable is used to predict the dependent variable is called

(A) a simple linear regression model

(B) a multiple regression models

(C) an independent model

(D) none of the above

(E) a simple linear regression model

(F) a multiple regression models

(G) an independent model

(H) none of the above

Correct Answer

(C) an independent model
(G) an independent model

[#49] If you use an ensemble of different base models, is it necessary to tune the hyper parameters of all base models to improve the ensemble performance?

(A) Yes

(B) No

(C) Yes

(D) No

Correct Answer

(B) No
(D) No

[#50] SVMxa0algorithmsxa0usexa0a set of mathematical functions that are defined as thexa0kernel.

(A) TRUE

(B) FALSE

(C) TRUE

(D) FALSE

Correct Answer

(A) TRUE
(C) TRUE

Machine Learning - Study Mode

[#46] Suppose you have trained an SVM with linear decision boundary after training SVM, you correctly infer that your SVM model is under fitting. Which of the following is best option would you more likely to consider iterating SVM next time?

Correct Answer

[#47] How many coefficients do you need to estimate in a simple linear regression model (One independent variable)?

Correct Answer

[#48] A regression model in which more than one independent variable is used to predict the dependent variable is called

Correct Answer

[#49] If you use an ensemble of different base models, is it necessary to tune the hyper parameters of all base models to improve the ensemble performance?

Correct Answer

[#50] SVMxa0algorithmsxa0usexa0a set of mathematical functions that are defined as thexa0kernel.

Correct Answer