** Introduction to Machine Learning Week 1 Nptel Assignment Answer**

*1 point*

Which of the following is/are unsupervised learning problem(s)?

*1 point*

Which of the following statement(s) about Reinforcement Learning (RL) is/are true?

*1 point*

Which of the following is/are classification tasks(s)?

*1 point*

Which of the following is/are regression task(s)?

*1 point*

Consider the following dataset. Fit a linear regression model of the form y=Î²0+Î²1x1+Î²2x2 $\ufffd={\ufffd}_{0}+{\ufffd}_{1}{\ufffd}_{1}+{\ufffd}_{2}{\ufffd}_{2}$ using the mean-squared error loss. Using this model, the predicted value of y $\ufffd$ at the point (x1,x2)=(0.5,−1.0) $({\ufffd}_{1},{\ufffd}_{2})=(0.5,-1.0)$ is

*1 point*

Consider the following dataset. Using a k-nearest neighbour (k-NN) regression model with k=3 $\ufffd=3$, predict the value of y at (x1,x2)=(0.5,−1.0) $({\ufffd}_{1},{\ufffd}_{2})=(0.5,-1.0)$. Use the Euclidean distance to find the nearest neighbours.

*1 point*

Consider the following statements regarding linear regression and k-NN regression models. Select the true statements.

*1 point*

Consider a binary classification problem where we are given certain measurements from a blood test and need to predict whether the patient does not have a particular disease (class 0) or has the disease (class 1). In this problem, false negatives (incorrectly predicting that the patient is healthy) have more serious consequences as compared to false positives (incorrectly predicting that the patient has the disease). Which of the following is an appropriate cost matrix for this classification problem? The row denotes the true class and the column denotes the predicted class.

*1 point*

Consider the following dataset with three classes: 0, 1 and 2. x1 and x2 are the independent variables whereas y is the class label. Using a k-NN classifier with k = 3, predict the class label at the point (x1,x2)=(0.7,−0.8) $({\ufffd}_{1},{\ufffd}_{2})=(0.7,-0.8)$. Use the Euclidean distance to find the nearest neighbours.

*1 point*

Suppose that we train two kinds of regression models corresponding to the following equations.

Which of the following statement(s) is/are correct?

- (i)
y=Î²0+Î²1x1+Î²2x2 $\ufffd={\ufffd}_{0}+{\ufffd}_{1}{\ufffd}_{1}+{\ufffd}_{2}{\ufffd}_{2}$ - (ii)
y=Î²0+Î²1x1+Î²2x2+Î²3x1x2 $\ufffd={\ufffd}_{0}+{\ufffd}_{1}{\ufffd}_{1}+{\ufffd}_{2}{\ufffd}_{2}+{\ufffd}_{3}{\ufffd}_{1}{\ufffd}_{2}$

Which of the following statement(s) is/are correct?

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