Reference no: EM133140872 , Length: word count:1500
Assessment Description
Rule-based classifiers use a set of "if-then" rules, R = {R1 ... Rm}, to match antecedents to consequents. A rule is typically expressed in the following form: IF Condition THEN Conclusion.
A decision tree may be viewed as a special case of a rule-based classifier, in which each path of the decision tree corresponds to a rule. For this assignment, you are going to apply decision tree and Naïve Bayes classification using the "Performance Decision Table."
Write a 1,250 to 1,500-word analysis. Let status be the class label attribute and include the following:
- Describe how you would modify the basic decision tree algorithm to take into consideration the count of each generalized data tuple (i.e., of each row entry).
- Use your algorithm to construct a decision tree from the given data.
- Given a data tuple having the values "systems," "26...30," and "46-50K" for the attributes department, age, and salary, respectively, what would a naïve Bayesian classification of the status for the tuple be? Research about probabilistic classification, which covers Naïve Bayes, and solve part (c).
Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.