Machine Learning - Practice Test

[#296] In following type of feature selection method we start with empty feature set

(A) forward feature selection

(B) backword feature selection

(C) both a and b

(D) none of the above

(E) forward feature selection

(F) backword feature selection

(G) both a and b

(H) none of the above

Correct Answer

(A) forward feature selection
(E) forward feature selection

[#297] Neural Networks are complex . . . . . . . . with many parameters.

(A) linear functions

(B) nonlinear functions

(C) discrete functions

(D) exponential functions

(E) linear functions

(F) nonlinear functions

(G) discrete functions

(H) exponential functions

Correct Answer

(A) linear functions
(E) linear functions

[#298] Which of the following assumptions do we make while deriving linear regression parameters? 1. The true relationship between dependent y and predictor x is linear 2. The model errors are statistically independent 3. The errors are normally distributed with a 0 mean and constant standard deviation 4. The predictor x is non-stochastic and is measured error-free

(A) 1, 2 and 3

(B) 1,3 and 4

(C) 1 and 3

(D) All of above

(E) 1, 2 and 3

(F) 1,3 and 4

(G) 1 and 3

(H) All of above

Correct Answer

(D) All of above
(H) All of above

[#299] For the given weather data, Calculate probability of not playing

(A) 0.4

(B) 0.64

(C) 0.36

(D) 0.5

(E) 0.4

(F) 0.64

(G) 0.36

(H) 0.5

Correct Answer

(C) 0.36
(G) 0.36

[#300] In PCA the number of input dimensiona are equal to principal components

(A) TRUE

(B) FALSE

(C) TRUE

(D) FALSE

Correct Answer

(A) TRUE
(C) TRUE

Machine Learning - Study Mode

[#296] In following type of feature selection method we start with empty feature set

Correct Answer

[#297] Neural Networks are complex . . . . . . . . with many parameters.

Correct Answer

Correct Answer

[#299] For the given weather data, Calculate probability of not playing

Correct Answer

[#300] In PCA the number of input dimensiona are equal to principal components

Correct Answer