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Student Loan Relational Data Set
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Abstract: Student Loan Relational Domain

Data Set Characteristics:  

Domain-Theory

Number of Instances:

1000

Area:

Social

Attribute Characteristics:

N/A

Number of Attributes:

N/A

Date Donated

1993-01-01

Associated Tasks:

N/A

Missing Values?

N/A

Number of Web Hits:

59990

Source:

Donor:

Michael J. Pazzani
University of California, Irvine
Irvine, CA USA


Data Set Information:

The predicate no_payment_due/1 is true for those people who are not required to repay a student loan. Auxiliary relations can be used to fully discriminate positive from negative instances of no_payment_due/1. Closed world assumption applies to all auxiliary relations.


Attribute Information:

N/A


Relevant Papers:

Pazzani, M., & Brunk, C. (1991). Detecting and correcting errors in rule-based expert systems: an integration of empirical and explanation-based learning. Knowledge Acquisition, 3, 157-173.
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