Q1: Topic: Naïve Bayes Classifier A patient goes to see a doctor. The doctor performs a test with 99% reliability - that is, 99% of people who are sick test positive and 99% of the healthy people test negative. The doctor knows that only 1 percent of the people in the country are sick. Now the question is: if the test comes out positive, is the probability of the patient actually being sick 99%? Q2: Topic: Naïve Bayes Classifier We have two classes: “spam” and “ham” (not spam). Training Data: Class: Ham D1: “good.” D2: “very good.” Class: Spam D3: “bad.” D4: “very bad.” D5: “very bad, very bad.” Test Data: Identify the class for the following document: D6: “good? bad! very bad!” Q3: Topic: Apriori Algorithm TID : items_bought T1 : { M,O,N,K,E,Y } T2 : { D,O,N,K,E,Y } T3 : { M,A,K,E } T4 : { M,U,C,K,Y } T5 : { C,O,O,K,I,E } Let minimum support = 60% And minimum confidence = 80% Find all frequent item sets using Apriori. Q4: Topic: Decision Tree Induction Create the decision tree for the following data: Outlook,Temperature,Humidity,Wind,Play Tennis Sunny,Hot,High,Weak,No Sunny,Hot,High,Strong,No Overcast,Hot,High,Weak,Yes Rain,Mild,High,Weak,Yes Rain,Cool,Normal,Weak,Yes Rain,Cool,Normal,Strong,No Overcast,Cool,Normal,Strong,Yes Sunny,Mild,High,Weak,No Sunny,Cool,Normal,Weak,Yes Rain,Mild,Normal,Weak,Yes Sunny,Mild,Normal,Strong,Yes Overcast,Mild,High,Strong,Yes Overcast,Hot,Normal,Weak,Yes Rain,Mild,High,Strong,No Q5: For Iris Flower dataset, show the correlation plots for each pair of attributes. Iris dataset comes in ARFF format alongside Weka tool.
Thursday, March 24, 2022
Machine Learning and Weka Interview (5 Questions)
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