Quiz Space

Machine Learning Practice · End Term · 13 Sept 2026 · May 2026 term

MLP End Term 13 Sept 2026 — Question 14

Question 14

+2 marksOne or more correct options

Select the false statements:

Select all that apply.

  1. A

    StandardScaler ensures the features correspond to a uniform distribution after scaling.

  2. B

    MinMaxScaler ensures that feature values follow a Gaussian Distribution

  3. C

    OridnalEncoder is best for data which contains values corresponding to a Normal Distribution.

  4. D

    Pipeline helps us apply separate transformations to numerical and categorical columns directly.

Show answer

Correct answers

  • A

    StandardScaler ensures the features correspond to a uniform distribution after scaling.

  • B

    MinMaxScaler ensures that feature values follow a Gaussian Distribution

  • C

    OridnalEncoder is best for data which contains values corresponding to a Normal Distribution.

  • D

    Pipeline helps us apply separate transformations to numerical and categorical columns directly.

See the whole paperTake it as a mock test

Question 14 of 30 in the IIT Madras BS Machine Learning Practice (MLP) End Term paper sat on 13 Sept 2026, in the May 2026 term (Machine Learning Practice 13 Sep 26). It carries 2 marks.

More questions from this paper

  1. Q1Consider the following pandas DataFrame representing employee training records: We want to retrieve all records of empl…
  2. Q2How many features remain in X_new after the transformation?
  3. Q3Determine the output of the following text preprocessing pipeline:
  4. Q4Four data points are given: A=(1,1), B=(2,2), C=(8,8), D=(10,10) A hierarchical agglomerative clustering algorithm usin…
  5. Q5A genre-based content recommender uses the 19 one-hot genre columns of each movie: Which of the following statements is…
  6. Q6What is the output of the following preprocessing pipeline code? (Round off to 2 decimal places if applicable)
  7. Q7Suppose the orginal dataset has 10 rows (1 to 10) Which row/rows of the dataset will be printed if the following code i…
  8. Q8Figure question
  9. Q9Consider a 3 class classification problem where the training dataset contains 10 features. The given model is trained o…
  10. Q10Assume both models in the code given below are fit on the same dataset (X_train) containing 10 features. Enter the diff…
  11. Q11What is the output of the following code? (Round Upto one decmimal) X = [[0], [1], [2], [3]] y = [0, 0, 1, 1] from skle…
  12. Q12Figure question
  13. Q13A binary classification model was evaluated on a test set with 500 samples. The model correctly identified 90 positive …
  14. Q15Which of the following metrics have their lower bound as 0?
  15. Q16Figure question
  16. Q17Consider the following implementation of PCA: Which of the following are correct?
  17. Q18Consider the following two ensemble regression architectures trained on the same dataset:
  18. Q19Consider the following code snippet: Which of the following holds true?
  19. Q20Consider the following assertion and reason. Select the correct option.\ Assertion (A): Increasing the number of estima…
  20. Q21An email service develops a machine learning model to automatically identify phishing emails.\ Any email predicted as p…
  21. Q22Which data augumentation operation is being perfomed on the input image in the given code?
  22. Q23Consider the following code: Assuming the all the models are trained on the same dataset, which of the models is likely…
  23. Q24A monthly airline-passenger series shows seasonal swings that grow larger as the overall level of the series rises over…
  24. Q25Identify the lines with errors in the given code snippet:
  25. Q26Select the correct statements regarding the following code snippet:
  26. Q27A company uses K-Means clustering to divide its customers into 4 groups based on their purchasing behavior. After train…
  27. Q28Identify which of the following lines (marked in comments) contain errors in the given code snippet:
  28. Q29Using user–user collaborative filtering, the predicted rating is
  29. Q30A forecasting model achieves an R2 score of 0.98 on the test set. However, it was trained using a feature that contains…