# 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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