NPTEL Introduction to Machine Learning Assignment Week 3 Answers

Are you looking for NPTEL Introduction to Machine Learning Assignment Week 3 Answers? If yes, you will find the answers to the questions asked in the NPTEL Introduction to Machine Learning quiz exam here. If you are preparing for this exam this article will help you in finding the latest and updated answers.

There is a total of 9 questions related to Linear Classification, Logistic Regression, and Linear Discriminant Analysis. The correct answers are marked in Green Color with a tick sign.

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NPTEL Introduction to Machine Learning Assignment Week 3 Answers

1. Which of the following is true about a logistic regression based classifier?

1. The logistic function is non-lingar in the weights
2. The logistic function is linear in the welghts
3. The decision boundary is linear in the weights
4. The decision boundary is non-linear in the weights

2. For a binary classification problem, the decision boundary resulting from the use of logistic regression is

1. linear
2. sigmoid
3. parabolic
4. exponential

3. Consider the case where two classes follow Gaussian distribution which are centered at (-1, 2) and (1, 4) and have identity covariance matrix. Which of the following is the separating decision boundary using LDA?

1. y-x = 3
2. x+y = 3
3. x+y = 6
4. (b) and (c) are possible
5. None of these
6. Can not be found from the given information

4. Consider the following relation between a dependent variable and an independent variable identified by doing simple linear regression. Which among the following relations between the two variables does the graph indicate?

1. as the independent variable increases, so does the dependent variable
2. as the independent variable increases, the dependent variable decreases
3. if an increase in the value of the dependent variable is observed then the independent variable will show a corresponding increase
4. if an increase in the value of the dependent variable is observed, then the independent variable Will show a corresponding decrease
5. the dependent variable in this graph does not actually depend on the independent variable
6. none of the above

5. Given the following distribution of data points:

What method would you choose to perform Dimensionality Reduction?

1. Linear Discriminant Analysis
2. Principal Component Analysis

6. In general, which of the following classification methods is the most resistant to gross outliers?

1. Quadratic Discriminant Analysis (QDA)
2. Linear Regression
3. Logistic regression
4. Linear Discriminant Analysis (LDA)

7. Suppose that we have two variables, X and Y (the dependent variable). We wish to find the relation between them. An expert tells us that relation between the two has the form Y = mX² +c. Available to us are samples of the variables X and Y. Is it possible to apply linear regression to this data to estimate the values of m and c?

1. no
2. yes
3. insutficient information

8. In a binary classification scenario where x Is the independent variable and y Is the dependent variable, logistic regression assumes that the conditional distribution y|x follows a

1. Bernoulli distribution
2. binomial distribution
3. normal distribution
4. exponential distribution

9. Consider the following data:

Assuming that you apply LDA to this data, what is the estimated covariance matrix?

1. [1.875 0.3125]
   [0.3125 0.9375]
2. [ 2.5 0.4167]
   [0.4167 1.25 ]
3. [1.875 0.3125]
   [0.3125 1.2188]
4. [ 2.5 0.4167]
   [0.4167 1.625 ]

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