CSC$691$ Assignment $2$

Decision Tree and Na$$ve Bayesian classification

The following table consists of training data from an employee database. The data have been generalized. For example, $"31$dots$35"$ for age represents the age range of $31$ to $35.$ For a given row entry, count represents the number of data tuples having the values for department, status, age, and salary given in that row.

$\backslash$table$[[$department$,$status,age,salary,count$],[$sales$,$senior,$31$dots$35,46$Kdots$50K,30],[$sales$,$junior,$26$dots$30,26$Kdots$30K,40],[$sales$,$junior,$31$dots$35,31$Kdots$35K,40],[$systems$,$junior,$21$dots$25,46$Kdots$50K,20],[$systems$,$senior,$31$dots$35,66$Kdots$70K,5],[$systems$,$junior,$26$dots$30,46$Kdots$50K,3],[$systems$,$senior,$41$dots$45,66$Kdots$70K,3],[$marketing$,$senior,$36$dots$40,46$Kdots$50K,10],[$marketing$,$junior,$31$dots$35,41$Kdots$45K,4],[$secretary$,$senior,$46$dots$50,36$Kdots$40K,4],[$secretary$,$junior,$26$dots$30,26$Kdots$30K,6]]$

Let status be the class label attribute.

$($a$)$ How would you modify the basic decision tree algorithm to take into consideration the 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," $"26..\mathrm{.}30,"$ and $"46-50K"$ for the attributes department, age, and salary, respectively, what would a na$$ve Bayesian classification of the status for the tuple be$?$