This is a set of 32 questions of Machine Learning MCQs. All questions and answers are based on our research and self-study. If you missed the latest MCQs post on our site please visit once.

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

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

**3.)** For which one of these relationships could we use regression analysis? Chose the correct one

**4.)** Which clustering technique requires prior knowledge of the number of clusters required?

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

**6.)** Which methodology works with clear margins of separation points?

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

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

**9.)** Which of them, best represents the property of Kernel?

**10.)** The main difficulty with using a regression line to analyze these data is *____*

**11.)** SVM uses which method for pattern analysis in High dimensional space?

**12.**) Which of the following is not example of Clustering?

**13.)** Which type of the clustering could handle Big Data?

**14.)** What are different types of Supervised learning

**15.)** Now Can you make a quick guess where the Decision tree will fall into *__*

**16.)** Correlation and regression are concerned with the relationship between _

**17.)** Does Logistic regression check for the linear relationship between dependent and independent variables ?

**18.)** 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

**19.)** Kernel methods can be used for supervised and unsupervised problems

**20.)**While running the same algorithm multiple times, which algorithm produces the same results?

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

**22.)** The main problem with using a single regression line

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

**24.)** The standard approach to supervised learning is to split the set of examples into the training set and the test

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

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

**27.)** Objective of unsupervised data covers all these aspects except

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

**29.)** What is the benefit of Naïve Bayes?

**30.)** The model which is widely used for the classification is

**31.)** The correlation between two variables is given by r = 0.0. . Which means

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

**Answer Sheet of Machine Learning MCQs**

Question Number | Question Answer |

1.) | Answer.) super |

2.) | Answer.) Logistic |

3.) | Answer.) HEIGHT |

4.) | Answer.) k means |

5.) | Answer.) supervised |

6.) | Answer.) SVM |

7.) | Answer.) kernel |

8.) | Answer.) linear or non linear |

9.) | Answer.) Converge |

10.) | Answer.) one or more |

11.) | Answer.) kernel |

12.) | Answer.) RFM |

13.) | Answer.) k means |

14.) | Answer.) regression and class |

15.) | Answer.) supervised |

16.) | Answer.) 2 quant |

17.) | Answer.) FALSE |

18.) | Answer.) all |

19.) | Answer.) TRUE |

20.) | Answer.) Hierarchical |

21.) | Answer.) Underfitting |

22.) | Answer.) Merging |

23.) | Answer.) TRUE |

24.) | Answer.) TRUE |

25.) | Answer.) Multi Linear |

26.) | Answer.) Classification becomes difficult |

27.) | Answer.) find clusters of data |

28.) | Answer.) Linear Regression |

29.) | Answer.) can process |

30.) | Answer.) Multi Linear |

31.) | Answer.) All the points |

32.) | Answer.) TRUE |

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