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17 Data Sets

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1. Annealing: Steel annealing data

2. Credit Approval: This data concerns credit card applications; good mix of attributes

3. Statlog (Australian Credit Approval): This file concerns credit card applications. This database exists elsewhere in the repository (Credit Screening Database) in a slightly different form

4. Statlog (Heart): This dataset is a heart disease database similar to a database already present in the repository (Heart Disease databases) but in a slightly different form

5. Hepatitis: From G.Gong: CMU; Mostly Boolean or numeric-valued attribute types; Includes cost data (donated by Peter Turney)

6. Echocardiogram: Data for classifying if patients will survive for at least one year after a heart attack

7. Horse Colic: Well documented attributes; 368 instances with 28 attributes (continuous, discrete, and nominal); 30% missing values

8. Flags: From Collins Gem Guide to Flags, 1986

9. Zoo: Artificial, 7 classes of animals

10. Pittsburgh Bridges: Bridges database that has original and numeric-discretized datasets

11. Statlog (German Credit Data): This dataset classifies people described by a set of attributes as good or bad credit risks. Comes in two formats (one all numeric). Also comes with a cost matrix

12. Cylinder Bands: Used in decision tree induction for mitigating process delays known as "cylinder bands" in rotogravure printing

13. Meta-data: Meta-Data was used in order to give advice about which classification method is appropriate for a particular dataset (taken from results of Statlog project).

14. Teaching Assistant Evaluation: The data consist of evaluations of teaching performance; scores are "low", "medium", or "high"

15. Arrhythmia: Distinguish between the presence and absence of cardiac arrhythmia and classify it in one of the 16 groups.

16. Dermatology: Aim for this dataset is to determine the type of Eryhemato-Squamous Disease.

17. Acute Inflammations: The data was created by a medical expert as a data set to test the expert system, which will perform the presumptive diagnosis of two diseases of the urinary system.