4. Reconsider the tennis playing training examples, if B Bayesian Belief Network depicting the conditional independence...
An example for Playing Tennis in machine learning: Attributes are Outlook, Temperature, Humidity and Wind. Data set and some statistics are already calculated below: Day Outlook Temperature Humidity Wind Mlay Tennis DI Sunny D2 Sunny D3 Ov ercast D4 Rain DS Rain D6 Rain D7 Overast DS Sunny D9 Sunny DIO Rain DI Sunny DI2 Overcast D13 Ovencast D1411 Rain Hot Hot Hot Mild Cool Cool Cool Mild Cool Mild Mild Mild High Weak High Strong No High Weak ligh...
Given the following six instances each with five attributes (Outlook, Temperature, Humidity, Wind, Day) and one class label, calculate Entropy of the whole system • calculate Information gain for attribute "Outlook" • calculate Gini-index for attribute "Outlook" • What is the information gain and Gini-index for attribute “Day Explain why “Day" is NOT a good feature being used as the root node of a decision tree. How to avoid using “Day” as the root node to create the tree ID...
. Question 3 (5 pts]: Given the following six instances cach with five attributes (Outlook, Temperature, Humidity, Wind, Day) and one class label, calculate Entropy of the whole system [1 pt] • calculate Information gain for attribute "Outlook" [1 pt] • calculate Gini-index for attribute "Outlook" [1 pt] What is the information gain and Gini-index for attribute "Day" [pt] • Explain why "Day" is NOT a good feature being used as the root node of a decision tree. How to...
please provide detailed solution.. Page 4 of S Exercise 2. Weather Prediction Using Bayes Classifier 15 marks Imagine that you are given the following set of training examples. Training Data Play Tennis No Outlookk Temperature Humadity Wind Day 1 85 80 Day 4 Day 5 Day 6 Da Day 8 Day 9 Day 10 Day 11 Sun Sunn Overcast Rain Rain Rain Overcast Sunn Sun Rain Sunn Overcast Overcast Rain Weak Stron Weak Weak Weak Stron Stron Weak Weak Weak...