Machine Learning Axioms MCQs Solution | TCS Fresco Play


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1. If you have a basket of different fruit varieties with some prior information on size, color, shape of each and every fruit . Which learning methodology is best applicable?

Supervised Learning  --  Correct

2. Do you think heuristic for rule learning and heuristics for decision trees are both same ?

False  --  Correct

3. What is the benefit of Naïve Bayes ?

Requires less training data  --  Correct

4. What is the advantage of using an iterative algorithm like gradient descent ? (select the best)

For Nonlinear regression problems, there is no closed form solution  --  Correct

5. For which one of these relationships could we use a regression analysis? Choose the correct one

Relationship between Height & weight (both Quantitative)  --  Correct

6. Does Logistic regression check for the linear relationship between dependent and independent variables ?

False  --  Correct

7. Which helps SVM to implement the algorithm in high dimensional space?

Kernel  --  Correct

8. Kernel methods can be used for supervised and unsupervised problems

True  --  Correct

9. Perceptron is _______________

a single layer feed-forward neural network  --  Correct

10. While running the same algorithm multiple times, which algorithm produces same results?

Hierarchical clustering  --  Correct


11. SVM will not perform well with large data set because (select the best answer)

classification becomes difficult , Difficult to simulate model, Lot of noise in data  --  Wrong training time is high --  selected

12. In a scenario, where the statistical model describes random error or noise instead of underlying relationship, what happens

Overfitting  --  Correct

13. Consider a regression equation, Now which of the following could not be answered by regression?

Estimate whether the association is linear or non-linear  --  Correct

14. Now Can you make quick guess where Decision tree will fall into _____ 

Supervised Learning  --  Correct

15. The main difficulty with using a regression line to analyze these data is ________________

presence of 1 or more outliers  --  Correct

16. For which one of these relationships could we use a regression analysis? Chose the correct one

Relationship between Height & weight (both Quantitative)  --  Correct

17. The correlation between two variables is given by r = 0.0. . This means

The best straight line through the data is horizontal.  --  Correct

18. Which of the following is not example of Clustering?

Market segmentation , Anomaly detection , Image segmentation --  Wrong --  selected

19. Most famous technique used in Text mining is

Naive Bayes  --  Correct

20. Disadvantage of Neural network according to your purview is

takes long time to be trained  --  Correct

21. One has to run through ALL the samples in your training set to do a single update for a parameter in a particular iteration. This is applicable for

Gradient Descent  --  Correct

22. Which type of the clustering could handle Big Data?

K Means clustering  --  Correct

23. Effect of outlier on the correlation coefficient ______________

An outlier might either decrease or increase a correlation coefficient, depending on where it is in relation to the other points  --  Correct

24. If the outcome is continuous, which model to be applied?

Multi-Linear Regression  --  Correct

25. SVM uses which method for pattern analysis in High dimensional space?

Kernel  --  Correct

26. The model which is widely used for the classification is

Segmentation  --  Wrong

27. Objective of unsupervised data covers all these aspect except

low-dimensional representations of the data , find clusters of the data , detect interesting coordinates and correlations, trace interesting directions in data --  Wrong --  selected

28. Correlation and regression are concerned with the relationship between _________

2 quantitative variables  --  Correct

29. Which model helps SVM to implement the algorithm in high dimensional space?

Kernel  --  Correct

30. In Kernel trick method, We do not need the coordinates of the data in the feature space

True  --  Correct

31. What are different types of Supervised learning

regression and classification  --  Correct

32. Which methodology works with clear margins of separation points?

Support Vector Machine  --  Correct

33. Which of the learning methodology applies conditional probability of all the variables with respective the dependent variable?

Supervised Learning --  Correct

34. The main problem with using single regression line

presence of 1 or more outliers  --  Correct

35. What are the advantages of neural networks (i) ability to learn by example (ii) fault tolerant (iii) suited for real time operation due to their high 'computational' rates

All the options are correct  --  Correct

36. Which clustering technique requires prior knowledge of the number of clusters required?

K Means clustering  --  Correct

37. Which technique implicitly defines the class of possible patterns by introducing a notion of similarity between data?

SVM , Multi-Linear Regression , Hierarchical clustering, Linear Regression  --  Wrong

 --  selected

38. Which of them, best represents the property of Kernel?

Modularity  --  Correct

39. The model in which one estimates the probability that the outcome variable assumes a certain value, rather than estimating the value itself.

Logistic Regression --  Correct

40. If the outcome is binary(0/1), which model to be applied?

Logistic Regression  --  Correct

41. SVM will not perform well with data with more noise because (select the best answer)

target classes could overlap  --  correct

42. The standard approach to supervised learning is to split the set of example into the training set and the test

True  --  Correct

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