NPTEL Deep Learning – IIT Ropar Week 5 Assignment Answers 2025
1. Which of the following is the most appropriate description of the method used in PCA to achieve dimensionality reduction?
- PCA achieves this by discarding a random subset of features in the dataset
- PCA achieves this by selecting those features in the dataset along which the variance of the dataset is maximised
- PCA achieves this by retaining the those features in the dataset along which the variance of the dataset is minimised
- PCA achieves this by looking for those directions in the feature space along which the variance of the dataset is maximised
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2. What is/are the limitations of PCA?
- It can only identify linear relationships in the data.
- It can be sensitive to outliers in the data.
- It is computationally less efficient than autoencoders
- It can only reduce the dimensionality of a dataset by a fixed amount.
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3. The following are possible numbers of linearly independent eigenvectors for a 7×7 matrix. Choose the incorrect option.
- 1
- 3
- 9
- 5
- 8
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4.
- σ1=10,σ2=5
- σ1=1,σ2=0
- σ1=100,σ2=25
- σ1=σ2=0
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5.
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6. What is the mean of the given data points x1,x2, x3 ?
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7.
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8. The maximum eigenvalue of the covariance matrix C is:
- 1
- 5.33
- 0.44
- 0.5
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9. The eigenvector corresponding to the maximum eigenvalue of the given matrix C is:
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10. Given that A is a 2×2 matrix, what is the determinant of A, if its eigenvalues are 6 and 7 ?
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