Machine learning Archives

1. In the last decade, many researchers started training bigger and bigger models, built with several different layers that’s why this approach is called . . . . . . . .

Deep learning

Machine learning

Reinforcement learning

Unsupervised learning

Detailed SolutionIn the last decade, many researchers started training bigger and bigger models, built with several different layers that’s why this approach is called . . . . . . . .

2. his clustering approach initially assumes that each data instance represents a single cluster.

expectation maximization

k-means clustering

agglomerative clustering

conceptual clustering

Detailed Solutionhis clustering approach initially assumes that each data instance represents a single cluster.

3. what is the function of ‘Supervised Learning’?

classifications, predict time series, annotate strings

speech recognition, regression

both a and b

none of above

Detailed Solutionwhat is the function of ‘Supervised Learning’?

4. Classification rules are extracted from . . . . . . . .

decision tree

root node

branches

siblings

Detailed SolutionClassification rules are extracted from . . . . . . . .

5. Which of the following are supervised learning applications

Spam detection, Pattern detection, Natural Language Processing

Image classification, Real-time visual tracking

Autonomous car driving, Logistic optimization

Bioinformatics, Speech recognition

Detailed SolutionWhich of the following are supervised learning applications

6. In Apriori algorithm, if 1 item-sets are 100, then the number of candidate 2 item-sets are

100

200

4950

5000

Detailed SolutionIn Apriori algorithm, if 1 item-sets are 100, then the number of candidate 2 item-sets are

7. What is/are true about kernel in SVM? 1. Kernel function map low dimensional data to high dimensional space 2. It’s a similarity function

1 and 2

None of these

Detailed SolutionWhat is/are true about kernel in SVM? 1. Kernel function map low dimensional data to high dimensional space 2. It’s a similarity function

8. The F-test

an omnibus test

considers the reduction in error when moving from the complete model to the reduced model

considers the reduction in error when moving from the reduced model to the complete model

can only be conceptualized as a reduction in error

Detailed SolutionThe F-test

9. In the regression equation Y = 75.65 + 0.50X, the intercept is

0.5

75.65

indeterminable

Detailed SolutionIn the regression equation Y = 75.65 + 0.50X, the intercept is

10. In the example of predicting number of babies based on stork’s population ,Number of babies is

outcome

feature

observation

attribute

Detailed SolutionIn the example of predicting number of babies based on stork’s population ,Number of babies is

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