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Considering the training set data presented in Annex 1, perform the following tasks:

1.       Build a decision tree based on the training set data, using the algorithm provided in the lecture, considering all attributes as possible classification  attributes, and as attribute selection method use the information gain.

2.       Apply the naïve Bayesian classification on the training data set in Annex 1, and classify this new data "Senior person with job, doesn't own a house and has good credit rating" with both the Bayesian classifier as well as the decision  tree obtained in a).

 

Annex 1

 

Age

Has job

Owns house

Credit rating

Approve loan

 

 

 

 

 

Young

False

False

Fair

No

Young

False

False

Good

No

Young

True

False

Good

Yes

Young

True

True

Fair

Yes

Young

False

False

Fair

No

Middle

False

False

Fair

No

Middle

False

False

Good

No

Middle

True

True

Good

Yes

Middle

False

True

Excellent

Yes

Middle

False

True

Excellent

Yes

Old

False

True

Excellent

Yes

Old

False

True

Good

Yes

Old

True

False

Good

Yes

Old

True

False

Excellent

Yes

Old

False

False

Fair

No

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