data mining

Jul 5th, 2016
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home work

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CMP 627 Data MiningCMP 627 Data MiningWeek 5 Homework Assignment 21CMP 627 Data Mining1. The following table consists of training data from an employee database. Thedata have been generalized. For example, "31...35" for age represents the agerange of 31 to 35. For a given row entry, count represents the number of datatuples having the values for department, status, age, and salary given in thatrow.DepartmentStatusAgeSalaryCountSalesSenior31..3546K.50K30SalesJunior26..3026K..30K40SalesJunior313531K..35K40SystemsJunior212546K.50K20SystemsSenior31.3566K.70K5SystemsJunior26.3046K..50K3SystemsSenior41..4566K.70K3MarketingSenior36.4046K.50K10MarketingJunior31..3541K45K4SecretarySenior46.5036K..40K4SecretaryJunior26.3026K.30K6Let status be the class label attribute.(a). How would you modify the basic decision tree algorithm to take into considerationthe count of each generalized data tuple (i.e., of each row entry)?(b). Use your algorithm to construct a decision tree from the given data.(c). Given a data tuple having the values "systems", "26....30", and "46K....50K" for theattributes department, age and salary respectively. What would a naive Bayesianclassification of the status for the tuple be?Answer.2CMP 627 Data Mining(a). The modified basic decis

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