Download Predictive Analytics: End Semester Examination Questions and Answers and more Exercises Applied Mathematics in PDF only on Docsity!
1 a) [4] CO4 L
1 b) [3] CO4 L
1 c) [3] CO4 L
2 a) [6] CO5 L
END SEMESTER EXAMINATION
MIT ACADEMY OF ENGINEERING
20 May 2022 TY BTECH SEMESTER - VI 2021 - 2022 BACKLOG EXAMINATION
PREDICTIVE ANALYTICS
TIME : 2 HOURS MAX MARKS : 50
- Non programmable scientific calculators are allowed
- Black figures to the right indicate full marks
INSTRUCTIONS TO CANDIDATES:
- Assume suitable data wherever necessary
TOTAL NO OF QUESTIONS:3 TOTAL NO OF PRINTED PAGES:
COURSE CODE: CS331T
What is Reinforcement Learning? [1 mark] What are the elements of it? [2 marks] Or What is deep learning? [1 mark] What are different types of Deep learning? [2 marks]
Explain the terminologies of ANN: 1.Weights [1 mark]
- Bias [1 mark]
- Activation function [1 mark]
- Learning Rate [1 mark] What are the strenghts and weaknesses of Artificial Neural Network. [ 3 strenghts -1.5 marks, 3 weaknesses,1.5 marks]
DEPARTMENT OF COMPUTER ENGINEERING
Write three methods to decide the values of' K' in K Means algorithm.
2 b) [8] CO5 L
3 a) We have two basketball teams named as A team and [10] CO5 L B team. Both the teams have played five tournaments each. In each tournament there are 10 matches are played. For every match played has a Winner (W) or Looser (L). If we know records of both the teams then we can easily conclude the probability of winning for A as well as for B. But If we do not have the names of the teams played but just have the records of play ,then how will you find the out the probabilities of winning for both the teams? Solve this problem using the data given in the table and use Expectation maximization method up-to one complete iteration. Step wise explanation is required. [each step carries 1 mark]
Following is the example of Academic grades ( A) and Offered salary package during placement ( B). Make the two clusters using K mediods algorithm ( K=2). Step by step solution is expectated. [ each step carries 1 mark]
Consider the following Dataset, and Create the stumps for the given dataset using Adaboost method using proper steps. [ 5 marks] [Each step carries 1/2 mark]
Use the following diagram to give answeres using HMM. State the HMM Property. [1 mark] Make the Transition probability matrix.[2 marks] Make the Emersion Proability Matrix. [2 marks] What is joint probabilty? [1 mark]
L
d) [6] CO6 L
c) [6] CO
