Develop a decision tree for the given data set.
Age |
Job |
House |
Credit |
Loan Approved |
Middle |
FALSE |
No |
Fair |
No |
Middle |
FALSE |
No |
Good |
No |
Middle |
FALSE |
Yes |
Excellent |
Yes |
Middle |
FALSE |
Yes |
Excellent |
Yes |
Middle |
TRUE |
Yes |
Good |
Yes |
Old |
TRUE |
No |
Excellent |
Yes |
Old |
FALSE |
No |
Fair |
No |
Old |
TRUE |
No |
Good |
Yes |
Old |
FALSE |
Yes |
Excellent |
Yes |
Old |
FALSE |
Yes |
Good |
Yes |
Young |
FALSE |
No |
Fair |
No |
Young |
FALSE |
No |
Fair |
No |
Young |
FALSE |
No |
Good |
No |
Young |
TRUE |
No |
Good |
Yes |
Young |
TRUE |
Yes |
Fair |
Yes |
Below is photo of Decision Tree for given dataset for Loan
Approved:
Here Loan approved is dependent on Age, House, Credit and Job factor.
If Age is Middle and have house -> Yes
If Age is Middle and don't have house -> No
If Age is Old and Credit is Fair -> No
If Age is Old and Credit is Good -> Yes
If Age is Old and Credit is Excellent -> Yes
If Age is Young and Have Job -> Yes
If Age is Young and don't have Job -> No
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