### NPTEL INTRODUCTION TO MACHINE LEARNING ASSIGNMENT 8

**These are the solutions of NPTEL INTRODUCTION TO MACHINE LEARNING ASSIGNMENT 8 WEEK 8**

**These are the solutions of NPTEL INTRODUCTION TO MACHINE LEARNING ASSIGNMENT 8 WEEK 8**

Course Name: INTRODUCTION TO MACHINE LEARNING

Link to Enroll: Click Here

**Q1. The figure below shows a Bayesian Network with 9 variables, all of which are binary.****Which of the following is/are always true for the above Bayesian Network?**

a. P(A,B|G)=P(A|G)P(B|G)P(A,B|G)=P(A|G)P(B|G)

b. P(A,I)=P(A)P(I)P(A,I)=P(A)P(I)

c. P(B,H|E,G)=P(B|E,G)P(H|E,G)P(B,H|E,G)=P(B|E,G)P(H|E,G)

d. P(C|B,F)=P(C|F)P(C|B,F)=P(C|F)

**Answer: c, d**

**Q2. Consider the following data for 20 budget phones, 30 mid-range phones, and 20 high-end phones:Consider a phone with 2 SIM card slots and NFC but no 5G compatibility. Calculate the probabilities of this phone being a budget phone, a mid-range phone, and a high-end phone using the Naive Bayes method. The correct ordering of the phone type from the highest to the lowest probability is?**

a. Budget, Mid-Range, High End

b. Budget, High End, Mid-Range

c. Mid-Range, High End, Budget

d. High End, Mid-Range, Budget

**Answer: c. Mid-Range, High End, Budget**

**These are the solutions of NPTEL INTRODUCTION TO MACHINE LEARNING ASSIGNMENT 8 WEEK 8**

**Q3. Consider the following dataset where outlook, temperature, humidity, and wind are independent features, and play is the dependent feature.****Find the probability that the student will not play given that x = (Outlook=sunny, Temperature=66, Humidity=90, Windy=True) using the Naive Bayes method. (Assume the continuous features are represented as Gaussian distributions).**

a. 0.0001367

b. 0.0000358

c. 0.0000236

d. 1

**Answer: c. 0.0000236**

**Q4. Which among Gradient Boosting and AdaBoost is less susceptible to outliers considering their respective loss functions?**

a. AdaBoost

b. Gradient Boost

c. On average, both are equally susceptible.

**Answer: b. Gradient Boost**

**These are the solutions of NPTEL INTRODUCTION TO MACHINE LEARNING ASSIGNMENT 8 WEEK 8**

**Q5. How do you prevent overfitting in random forest models?**

a. Increasing Tree Depth.

b. Increasing the number of variables sampled at each split.

c. Increasing the number of trees.

d. All of the above.

**Answer: d. All of the above.**

**Q6. A dataset with two classes is plotted below.****Does the data satisfy the Naive Bayes assumption?**

a. Yes

b. No

c. The given data is insufficient

d. None of these

**Answer: a. Yes**

**These are the solutions of NPTEL INTRODUCTION TO MACHINE LEARNING ASSIGNMENT 8 WEEK 8**

**Q7. Ensembling in random forest classifier helps in achieving:**

a. reduction of bias error

b. reduction of variance error

c. reduction of data dimension

d. none of the above

**Answer: c. reduction of data dimension**

**These are the solutions of NPTEL INTRODUCTION TO MACHINE LEARNING ASSIGNMENT 8 WEEK 8**

More weeks solution of this course: https://progies.in/answers/nptel/introduction-to-machine-learning

More NPTEL Solutions: https://progies.in/answers/nptel

* The material and content uploaded on this website are for general information and reference purposes only. Please do it by your own first.