How you would modify the basic decision tree algorithm » Full Grade
Assignment Instructions
Save your time - order a paper!
Get your paper written from scratch within the tight deadline. Our service is a reliable solution to all your troubles. Place an order on any task and we will take care of it. You won’t have to worry about the quality and deadlines
Order Paper NowAssignment ID: FG133140872 , 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.
Looking for a Similar Assignment? Let us take care of your classwork while you enjoy your free time! All papers are written from scratch and are 100% Original. Try us today! Use Code FREE15
Chat with us on Whatsapp