Summary

(No information yet)

License

unknown (from Weka repository)

Dependencies

Tags

arff slurped Weka

Attribute Types

Integer,Floating Point,String

Download

# Instances: 155 / # Attributes: 20
HDF5 (113.3 KB) XML CSV ARFF LibSVM Matlab Octave

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Original Data Format

arff

Name

hepatitis

Version mldata

0

Comment

1. Title: Hepatitis Domain

2. Sources: (a) unknown (b) Donor: G.Gong (Carnegie-Mellon University) via Bojan Cestnik Jozef Stefan Institute Jamova 39 61000 Ljubljana Yugoslavia (tel.: (38)(+61) 214-399 ext.287) } (c) Date: November, 1988

3. Past Usage:

   1. Diaconis,P. & Efron,B. (1983). Computer-Intensive Methods in Statistics. Scientific American, Volume 248. -- Gail Gong reported a 80% classfication accuracy
   2. Cestnik,G., Konenenko,I, & Bratko,I. (1987). Assistant-86: A Knowledge-Elicitation Tool for Sophisticated Users. In I.Bratko & N.Lavrac (Eds.) Progress in Machine Learning, 31-45, Sigma Press. -- Assistant-86: 83% accuracy

4. Relevant Information: Please ask Gail Gong for further information on this database.

5. Number of Instances: 155

6. Number of Attributes: 20 (including the class attribute)

7. Attribute information:

   1. Class: DIE, LIVE
   2. AGE: 10, 20, 30, 40, 50, 60, 70, 80
   3. SEX: male, female
   4. STEROID: no, yes
   5. ANTIVIRALS: no, yes
   6. FATIGUE: no, yes
   7. MALAISE: no, yes
   8. ANOREXIA: no, yes
   9. LIVER BIG: no, yes
   10. LIVER FIRM: no, yes
   11. SPLEEN PALPABLE: no, yes
   12. SPIDERS: no, yes
   13. ASCITES: no, yes
   14. VARICES: no, yes
   15. BILIRUBIN: 0.39, 0.80, 1.20, 2.00, 3.00, 4.00 -- see the note below
   16. ALK PHOSPHATE: 33, 80, 120, 160, 200, 250
   17. SGOT: 13, 100, 200, 300, 400, 500,
   18. ALBUMIN: 2.1, 3.0, 3.8, 4.5, 5.0, 6.0
   19. PROTIME: 10, 20, 30, 40, 50, 60, 70, 80, 90
   20. HISTOLOGY: no, yes

   The BILIRUBIN attribute appears to be continuously-valued. I checked this with the donater, Bojan Cestnik, who replied:

   About the hepatitis database and BILIRUBIN problem I would like to say the following: BILIRUBIN is continuous attribute (= the number of it's "values" in the ASDOHEPA.DAT file is negative!!!); "values" are quoted because when speaking about the continuous attribute there is no such thing as all possible values. However, they represent so called "boundary" values; according to these "boundary" values the attribute can be discretized. At the same time, because of the continious attribute, one can perform some other test since the continuous information is preserved. I hope that these lines have at least roughly answered your question.

8. Missing Attribute Values: (indicated by "?") Attribute Number: Number of Missing Values: 1: 0 2: 0 3: 0 4: 1 5: 0 6: 1 7: 1 8: 1 9: 10 10: 11 11: 5 12: 5 13: 5 14: 5 15: 6 16: 29 17: 4 18: 16 19: 67 20: 0

9. Class Distribution: DIE: 32 LIVE: 123

Relabeled values in attribute SEX From: 2 To: male
From: 1 To: female

Relabeled values in attribute STEROID From: 1 To: no
From: 2 To: yes

Relabeled values in attribute ANTIVIRALS From: 2 To: no
From: 1 To: yes

Relabeled values in attribute FATIGUE From: 2 To: no
From: 1 To: yes

Relabeled values in attribute MALAISE From: 2 To: no
From: 1 To: yes

Relabeled values in attribute ANOREXIA From: 2 To: no
From: 1 To: yes

Relabeled values in attribute LIVER_BIG From: 1 To: no
From: 2 To: yes

Relabeled values in attribute LIVER_FIRM From: 2 To: no
From: 1 To: yes

Relabeled values in attribute SPLEEN_PALPABLE From: 2 To: no
From: 1 To: yes

Relabeled values in attribute SPIDERS From: 2 To: no
From: 1 To: yes

Relabeled values in attribute ASCITES From: 2 To: no
From: 1 To: yes

Relabeled values in attribute VARICES From: 2 To: no
From: 1 To: yes

Relabeled values in attribute HISTOLOGY From: 1 To: no
From: 2 To: yes

Names

AGE,SEX,STEROID,ANTIVIRALS,FATIGUE,MALAISE,ANOREXIA,LIVER_BIG,LIVER_FIRM,SPLEEN_PALPABLE,

Types

1. numeric
2. nominal:male,female
3. nominal:no,yes
4. nominal:no,yes
5. nominal:no,yes
6. nominal:no,yes
7. nominal:no,yes
8. nominal:no,yes
9. nominal:no,yes
10. nominal:no,yes

Data (first 10 data points)

AGE	SEX	STER...	ANTI...	FATI...	MALA...	ANOR...	LIVE...	LIVE...	SPLE...	...
30	male	no	no	no	no	no	no	no	no	...
50	female	no	no	yes	no	no	no	no	no	...
78	female	yes	no	yes	no	no	yes	no	no	...
31	female	nan	yes	no	no	no	yes	no	no	...
34	female	yes	no	no	no	no	yes	no	no	...
34	female	yes	no	no	no	no	yes	no	no	...
51	female	no	no	yes	no	yes	yes	no	yes	...
23	female	yes	no	no	no	no	yes	no	no	...
39	female	yes	no	yes	no	no	yes	yes	no	...
30	female	yes	no	no	no	no	yes	no	no	...
...	...	...	...	...	...	...	...	...	...	...

Description

A jarfile containing 37 classification problems, originally obtained from the UCI repository (datasets-UCI.jar, 1,190,961 Bytes).

URLs

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Publications

Data Source

http://www.ics.uci.edu/~mlearn/MLRepository.html

Measurement Details

Usage Scenario

revision 1

by mldata on 2010-11-06 09:57

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