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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