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IIT M QUIZ 1 FOUNDATION DAD DIPLOMA QPD1 16 Oct 2022 - 16 Oct 2022

MLP Quiz 121 questions50 marks17 MCQ · 3 MSQ · 1 SAFoundation / Diploma / QPD1
Elapsed 00:00
Q1MCQ0 marks
question figure
  1. YES
  2. NO
Q2MCQ1 mark
The violin plot shown in Figure 2 demonstrates the age of passengers on the Titanic ship. Mark the approximate age range of most of the passengers. question figure The violin plot shown in Figure 2 demonstrates the age of passengers on the Titanic ship. Mark the approximate age range of most of the passengers.
  1. 20 - 40
  2. 80 above
  3. Less than 20
  4. 40-60
Q3MCQ2 marks
Which of the following Sklearn objects can help you to reduce, expand or generate feature representations?
  1. Estimator
  2. Predictor
  3. Transformer
  4. None of these
Q4MCQ2 marks
What will be the output of the following code? question figure What will be the output of the following code?
  1. question figure
  2. question figure
  3. question figure
  4. question figure
Q5MCQ2 marks
Go through the code snippet given below: question figure Go through the code snippet given below: What will be the shape of the feature matrix (X.shape) and the label vector (y.shape)?
  1. (2000, 12) and (1000, 6)
  2. (1, 1000) and (1,1000)
  3. (599, 1) and (699, 1)
  4. (1000, 6) and (1000,)
Q6MCQ2 marks
Which of the following options is likely to be the correct output of the code snippet given below? question figure Which of the following options is likely to be the correct output of the code snippet given below?
  1. question figure
  2. question figure
  3. question figure
  4. question figure
Q7MCQ2 marks
In the figure 1, what are the names of classes arranged in the increasing order of the median values? question figure In the figure 1, what are the names of classes arranged in the increasing order of the median values?
  1. First < Second < Third
  2. Third < Second < First
  3. Second < Third < First
  4. Third < First < Second
Q8MCQ2 marks
Go through the code snippet given below and mark the correct output. question figure Go through the code snippet given below and mark the correct output.
  1. 1
  2. 3
  3. 9
  4. 25
  5. 4
  6. 5
Q9MCQ2 marks
Which of the following is likely to be the correct output of the code given below? question figure Which of the following is likely to be the correct output of the code given below?
  1. 12
  2. 29
  3. No evaluation metrics are mentioned, hence it will produce an error
  4. 0.96
Q10MCQ3 marks
Which of the following is likely to be the correct output of the code given below? question figure Which of the following is likely to be the correct output of the code given below?
  1. question figure
  2. question figure
  3. question figure
  4. question figure
Q11MCQ3 marks
Consider the following code snippet: question figure Consider the following code snippet: Which of the following could be the correct output?
  1. question figure
  2. question figure
  3. question figure
  4. question figure
Q12MCQ3 marks
Which of the following options will be the correct output of print(clf.coef_)? question figure Which of the following options will be the correct output of print(clf.coef_)?
  1. [ 0.35 -0. -0. ]
  2. [-0.85,0]
  3. [3,2,1,2]
  4. Given code block will return an error.
Q13MCQ3 marks
Go through the code snippet given below and mark the correct output. question figure Go through the code snippet given below and mark the correct output.
  1. 0.61
  2. 0.83
  3. 0.95
  4. 1
  5. -0.6
  6. 5
Q14MCQ3 marks
Which of the following is likely to be the correct output of the code given below? question figure Which of the following is likely to be the correct output of the code given below?
  1. question figure
  2. question figure
  3. question figure
  4. question figure
Q15MCQ3 marks
Which of the following code blocks will correctly take the learning rate as‘optimal’ ?
  1. question figure
  2. question figure
  3. question figure
  4. question figure
Q16MSQ2 marksselect all that apply
Which of the following code blocks will correctly return an array of feature variables?
  1. question figure
  2. question figure
  3. question figure
  4. question figure
Q17MSQ3 marksselect all that apply
Scikit-Learn’s API is remarkably well designed. The main design principles are:-
  1. Nonproliferation of classes
  2. Sensible defaults
  3. Consistency
  4. Proportion
Q18MSQ3 marksselect all that apply
Go through the code block given below: question figure Go through the code block given below: Which of the following can’t be the correct output of the given code block?
  1. 0.0
  2. 0.01
  3. 0.1
  4. 1
Q19SA3 marks
Enter the correct output of the following code block. question figure Enter the correct output of the following code block.
Comprehension passage - the questions below it refer to this
Go through the code snippet given below and answer the given subquestions. question figure Go through the code snippet given below and answer the given subquestions.
Q20MCQ3 marks
Which of the following options will be the output of the given code?
  1. [-0.02634908 0.01189399 0.0917284 0.08966849]
  2. array([-0.22622766, -0.00582008, -0.1820344 , 0.03518086, -0.14490955])
  3. array([-0.22622766, -0.00582008, -0.1820344 ])
  4. Given code will return an error because the data set is not given
Q21MCQ3 marks
Which of the following could be the possible output of print(reg.score())?
  1. -0.528
  2. 1
  3. 0.528
  4. Given code will return an error

Answer key

  1. Q1 (MCQ, 0 marks): A
  2. Q2 (MCQ, 1 marks): A
  3. Q3 (MCQ, 2 marks): C
  4. Q4 (MCQ, 2 marks): A
  5. Q5 (MCQ, 2 marks): D
  6. Q6 (MCQ, 2 marks): A
  7. Q7 (MCQ, 2 marks): B
  8. Q8 (MCQ, 2 marks): F
  9. Q9 (MCQ, 2 marks): D
  10. Q10 (MCQ, 3 marks): B
  11. Q11 (MCQ, 3 marks): A
  12. Q12 (MCQ, 3 marks): A
  13. Q13 (MCQ, 3 marks): C
  14. Q14 (MCQ, 3 marks): D
  15. Q15 (MCQ, 3 marks): A
  16. Q16 (MSQ, 2 marks): B, D
  17. Q17 (MSQ, 3 marks): A, B, C
  18. Q18 (MSQ, 3 marks): B, C, D
  19. Q19 (SA, 3 marks): 6
  20. Q20 (MCQ, 3 marks): A
  21. Q21 (MCQ, 3 marks): D

Concepts this paper tests

Auto-generated summary from the source site. Handy as a checklist; the lessons above explain each idea from scratch.

Summary of Core Topics, Concepts, Principles, and Equations

1. Machine Learning Algorithms

2. Data Preprocessing

3. Model Evaluation

4. Data Splitting

5. Data Generation

6. Scikit-Learn API Design Principles

7. Equations

MSE=1n∑i=1n(yi−y^i)2\text{MSE} = \frac{1}{n} \sum_{i=1}^{n} (y_i - \hat{y}_i)^2
R2=1−∑i=1n(yi−y^i)2∑i=1n(yi−yˉ)2R^2 = 1 - \frac{\sum_{i=1}^{n} (y_i - \hat{y}_i)^2}{\sum_{i=1}^{n} (y_i - \bar{y})^2}
Cost Function=∑i=1n(yi−y^i)2+α∑j=1mθj2\text{Cost Function} = \sum_{i=1}^{n} (y_i - \hat{y}_i)^2 + \alpha \sum_{j=1}^{m} \theta_j^2
Cost Function=∑i=1n(yi−y^i)2+α∑j=1m∣θj∣\text{Cost Function} = \sum_{i=1}^{n} (y_i - \hat{y}_i)^2 + \alpha \sum_{j=1}^{m} |\theta_j|

Graph 1: Machine Learning Algorithms

Graph 2: Data Preprocessing

Graph 3: Model Evaluation

Graph 4: Data Splitting

Graph 5: Data Generation

Graph 6: Scikit-Learn API Design Principles

These graphs and summaries should help you understand the core topics and their relationships, which are essential for the exam.