Use Java / Project: Nave Bayesian Classifier

Implement (that is, code and execute) a Nave Bayes Classifier, incorporating attributes that are binary (e.g., home owner: yes, no), categorical (e.g., marital status: single, married, divorced), and continuous numeric (e.g., income: 100.5K, 96K, ...). Assume the class label is binary. Use a fixed number of attributes. Use the table in Fig 5.9 of the textbook as the training data. Test your classifier on the following test cases: (a) Home owner-yes, Marital status = Married, Income = 50.7K (b) All the cases in Fig. 5.9 (the same table) Use smoothing, if necessary. Implement (that is, code and execute) a Nave Bayes Classifier, incorporating attributes that are binary (e.g., home owner: yes, no), categorical (e.g., marital status: single, married, divorced), and continuous numeric (e.g., income: 100.5K, 96K, ...). Assume the class label is binary. Use a fixed number of attributes. Use the table in Fig 5.9 of the textbook as the training data. Test your classifier on the following test cases: (a) Home owner-yes, Marital status = Married, Income = 50.7K (b) All the cases in Fig. 5.9 (the same table) Use smoothing, if necessary