Machine Learning - Study Mode

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[#331] Features being classified is independent of each other in Nave Bayes Classifier

(A) FALSE

(B) TRUE

(C) FALSE

(D) TRUE

Correct Answer

(B) TRUE
(D) TRUE

[#332] What does learning exactly mean?

(A) robots are programed so that they can perform the task based on data they gather from sensors.

(B) a set of data is used to discover the potentially predictive relationship.

(C) learning is the ability to change according to external stimuli and remembering most of all previous experiences.

(D) it is a set of data is used to discover the potentially predictive relationship.

(E) robots are programed so that they can perform the task based on data they gather from sensors.

(F) a set of data is used to discover the potentially predictive relationship.

(G) learning is the ability to change according to external stimuli and remembering most of all previous experiences.

(H) it is a set of data is used to discover the potentially predictive relationship.

Correct Answer

(C) learning is the ability to change according to external stimuli and remembering most of all previous experiences.
(G) learning is the ability to change according to external stimuli and remembering most of all previous experiences.

[#333] What do you mean by a hard margin?

(A) the svm allows very low error in classification

(B) the svm allows high amount of error in classification

(C) both 1 & 2

(D) none of the above

(E) the svm allows very low error in classification

(F) the svm allows high amount of error in classification

(G) both 1 & 2

(H) none of the above

Correct Answer

(A) the svm allows very low error in classification
(E) the svm allows very low error in classification

[#334] Suppose your model is demonstrating high variance across the different training sets. Which of the following is NOT valid way to try and reduce the variance?

(A) increase the amount of traning data in each traning set

(B) improve the optimization algorithm being used for error minimization.

(C) decrease the model complexity

(D) reduce the noise in the training data

(E) increase the amount of traning data in each traning set

(F) improve the optimization algorithm being used for error minimization.

(G) decrease the model complexity

(H) reduce the noise in the training data

Correct Answer

(B) improve the optimization algorithm being used for error minimization.
(F) improve the optimization algorithm being used for error minimization.

[#335] The problem of finding hidden structure in unlabeled data is called . . . . . . . .

(A) supervised learning

(B) unsupervised learning

(C) reinforcement learning

(D) none of the above

(E) supervised learning

(F) unsupervised learning

(G) reinforcement learning

(H) none of the above

Correct Answer

(B) unsupervised learning
(F) unsupervised learning