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.
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Thursday, March 24, 2022
Machine Learning and Weka Interview (5 Questions)
Labels:
Machine Learning,
Technology,
Weka
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