# ML Deep Learning Fundamentals Applications Week 3 Answers

Are you searching for reliable **ML Deep Learning Fundamentals Applications Week 3 Answers 2024**? Look no further! Our solutions are designed to provide clear, detailed answers, helping you navigate your NPTEL course with confidence.

## Table of Contents

**ML Deep Learning Fundamentals Applications Week 3 Answers (July-Dec 2024)**

**Q1.The bandwidth parameter in the Parzen Window method determines:**

The number of neighbors to consider for classification

The size of the neighborhood around a test instance

The dimensionality of the feature space.

The complexity of the classifier

**Answer: Updating Soon (in progress)**

**Q2.If the number of data samples becomes very large.**

Bayesian Estimation is worse than MLE

Maximum Likelihood estimates are slightly bad

Bayesian Estimation performs same as MLE

None

**Answer: Updating Soon (in progress)**

**For answers or latest updates join our telegram channel: Click here to join **

**These are ML Deep Learning Fundamentals Applications Week 3 Answers**

**Q3. What happens when k=1 in k -Nearest Neighbor algorithm:**

Underfitting

Overfitting

High testing accuracy

All the above

**Answer: Updating Soon (in progress)**

**Q4. There are 18 points in an axis plane namely –[(0.8,0.8)t,(1,1)t,(1.2,0.8)t,(0.8,1.2)t,(1.2,1.2)t],belong to class 1;[(4,3)t,(3.8,2.8)t,(4.2,2.8)t,(3.8,3.2)t(4.2,3.2)t,(4.4,2.8)t,(4.4,4.4)t],belong to class 2;[(3.2,0.4)t,(3.2,0.7)t,(3.8,0.5)t,(3.5,1)t,(4,1)t,(4,0.7)t],belong to class 3.A new pointP=(4.2,1.8)tintroduces into the map. The point P belongs to which class? Use k-nearest neighbor technique with k=5to calculate the result.**

Class 1

Class 2

Class 3

None of the above

**Answer: Updating Soon (in progress)**

**For answers or latest updates join our telegram channel: Click here to join **

**These are ML Deep Learning Fundamentals Applications Week 3 Answers**

**Q5. Suppose we have two training data points located at 0.5 and 0.7, and we use 0.3 as its rectangle window width. Using the Parzen window technique, what would be the probability density if we assume the query point is 0.5?**

0.5

0.75

2.22

1.67

**Answer: Updating Soon (in progress)**

**Q6. Suppose that X is a discrete random variable with the following probabilitymass function: where is a parameter.(0≤θ≤1)**

The following 10 independent observations were taken from such a distribution:

(3,0,2,1,3,2,1,0,2,1)

. What is the maximum likelihood estimate of θ

?

2

1

0.5

0

Answer: Updating Soon (in progress)

**For answers or latest updates join our telegram channel: Click here to join **

**These are ML Deep Learning Fundamentals Applications Week 3 Answerss**

**Q7. Which of the following statements are true about k**

nearest neighbor (KNN)-

Odd value of “K” preferred over even values.

Does more computation on test time rather than train time.

Work well with high dimension.

The optimum value of K for KNN is highly independent on the data.

**Answer: Updating Soon (in progress)**

**Q8.The disadvantage of using k-NN as classifier:**

Fails while handling large dataset

Fails while handling small dataset

Sensitive to outliers

Training is required

**Answer: Updating Soon (in progress)**

**For answers or latest updates join our telegram channel: Click here to join **

**These are ML Deep Learning Fundamentals Applications Week 3 Answers**

**Q9. Consider single observation X that depends on a random parameter .Suppose θhas a prior distribution**

fθ(θ)=λe−λθforθ≥0,λ>0fxθ(x)=θe−θx|x|>0

Find the MAP estimation of θ

1λ+X

1λ−X

λX

X

**Answer: Updating Soon (in progress)**

**Q10.The MLE for the data samples X={x1,x2,…,xi,…,xk} with the Bernoulli distribution is**

n⋅xk

xkn

Mean of xi

None

**Answer: Updating Soon (in progress)**

**For answers or latest updates join our telegram channel: Click here to join **

**These are ML Deep Learning Fundamentals Applications Week 3 Answers**

All weeks of Introduction to Machine Learning: Click Here

More Nptel Courses: https://progiez.com/nptel-assignment-answers