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[#196] A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0.

(A) TRUE

(B) FALSE

(C) TRUE

(D) FALSE

Correct Answer

(A) TRUE
(C) TRUE

[#197] 8 observations are clustered into 3 clusters using K-Means clustering algorithm. After first iteration clusters, C1, C2, C3 has following observations: C1: {(2,2), (4,4), (6,6)} C2: {(0,4), (4,0),(2,5)} C3: {(5,5), (9,9)} What will be the cluster centroids if you want to proceed for second iteration?

(A) C1: (4,4), C2: (2,2), C3: (7,7)

(B) C1: (6,6), C2: (4,4), C3: (9,9)

(C) C1: (2,2), C2: (0,0), C3: (5,5)

(D) C1: (4,4), C2: (3,3), C3: (7,7)

(E) C1: (4,4), C2: (2,2), C3: (7,7)

(F) C1: (6,6), C2: (4,4), C3: (9,9)

(G) C1: (2,2), C2: (0,0), C3: (5,5)

(H) C1: (4,4), C2: (3,3), C3: (7,7)

Correct Answer

(D) C1: (4,4), C2: (3,3), C3: (7,7)
(H) C1: (4,4), C2: (3,3), C3: (7,7)

[#198] Any linear combination of the components of a multivariate Gaussian is a univariate Gaussian.

(A) TRUE

(B) FALSE

(C) TRUE

(D) FALSE

Correct Answer

(A) TRUE
(C) TRUE

[#199] The apriori property means

(A) if a set cannot pass a test, its supersets will also fail the same test

(B) to decrease the efficiency, do level-wise generation of frequent item sets

(C) to improve the efficiency, do level-wise generation of frequent item sets d.

(D) if a set can pass a test, its supersets will fail the same test

(E) if a set cannot pass a test, its supersets will also fail the same test

(F) to decrease the efficiency, do level-wise generation of frequent item sets

(G) to improve the efficiency, do level-wise generation of frequent item sets d.

(H) if a set can pass a test, its supersets will fail the same test

Correct Answer

(A) if a set cannot pass a test, its supersets will also fail the same test
(E) if a set cannot pass a test, its supersets will also fail the same test

[#200] In which neural net architecture, does weight sharing occur?

(A) recurrent neural network

(B) convolutional neural network

(C) . fully connected neural network

(D) both a and b

(E) recurrent neural network

(F) convolutional neural network

(G) . fully connected neural network

(H) both a and b

Correct Answer

(D) both a and b
(H) both a and b