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Machine Learning Techniques · End Term · May 2025 FN
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Q153 Q154 Q155 Q156 Q157 Q158 Q159 Q160 Q161 Q162 Q163 Q164 Q165 Q166 Q167 Q168 Q169 Question 153 MCQ · 3.0 marks 6406534706359. PCA has reduced the dimensionality of the dataset because the combinations
of features are de-correlated.
6406534706360. PCA has not reduced the dimensionality of the dataset because all principal
components are retained.
6406534706361. PCA always reduces the dimensionality of the dataset regardless of the
number of components retained.
6406534706362. PCA can never be used for dimensionality reduction.
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Question 154 MCQ · 3.0 marks 6406534706367. 6406534706368. 6406534706369. 6406534706370. A published solution is not available for this question yet.
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Question 155 MCQ · 4.0 marks 6406534706363. 6406534706364. 6406534706365. 6406534706366. A published solution is not available for this question yet.
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Question 156 MCQ · 2.0 marks A published solution is not available for this question yet.
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Question 157 MSQ · 3.0 marks Which among the following is TRUE for k-NN algorithm? Select all that apply.
6406534706375. 1-nearest neighbour is sensitive to outliers.
6406534706376. k-NN can only be applied to a classification problem.
6406534706377. As k increases, the model is more likely to overfit.
6406534706378. The bias increases with the increase in the value of k.
6406534706379. The variance increases with the increase in the value of k.
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Question 158 MSQ · 3.0 marks A published solution is not available for this question yet.
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Question 159 MSQ · 3.0 marks 6406534706388. 6406534706389. 6406534706390. 6406534706391. A published solution is not available for this question yet.
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Question 160 MSQ · 2.0 marks With respect to the Lloyd’s algorithm, choose the correct statements:
6406534706380. The partition configurations cannot repeat themselves.
6406534706381. After doing the reassignments (consider at least one point reassigned to the
new cluster), we might get the same means for all clusters.
6406534706382. Objective function after making the re-assignments strictly reduces.
6406534706383. Objective function after making the re-assignments strictly increases.
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Question 161 NAT · 3.0 marks A published solution is not available for this question yet.
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Question 162 NAT · 4.0 marks A published solution is not available for this question yet.
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Question 163 NAT · 4.0 marks A published solution is not available for this question yet.
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Question 164 MCQ · 4.0 marks
Based on the above data, answer the given subquestions.
6406534706395. 6406534706396. 6406534706397. 6406534706398. A published solution is not available for this question yet.
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Question 165 MCQ · 2.0 marks
Based on the above data, answer the given subquestions.
6406534706399. The coefficients shrinks towards zero.
6406534706400. The coefficients increases in magnitude.
6406534706401. The coefficients remain unchanged.
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Question 166 NAT · 3.0 marks
Based on the above data, answer the given subquestions.
What is the probability that a 60-year-old patient with a cholesterol level of 200 mg/dL has the
disease? Enter the answer correct to two decimal places.
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Question 167 NAT · 3.0 marks
Based on the above data, answer the given subquestions.
How high should the cholesterol level be for the patient mentioned in the previous question to
have a 50% chance of being diagnosed with the disease?
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Question 168 MCQ · 2.0 marks Consider the datapoints (−2,−2) with label +1 and (2, 2) with label −1. A hard margin SVM is applied
on this dataset. Answer the given subquestions:
Which of the following is the decision boundary for the given dataset?
6406534706404. 6406534706405. 6406534706406. 6406534706407. A published solution is not available for this question yet.
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Question 169 NAT · 2.0 marks Consider the datapoints (−2,−2) with label +1 and (2, 2) with label −1. A hard margin SVM is applied
on this dataset. Answer the given subquestions:
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