# Info on Primary Tumor Data Base

    Citation Request:
       This primary tumor domain was obtained from the University Medical Centre,
       Institute of Oncology, Ljubljana, Yugoslavia.  Thanks go to M. Zwitter and
       M. Soklic for providing the data.  Please include this citation if you plan
       to use this database.

    1. Title: Primary Tumor Domain

    2. Sources:
         (a) Source:
         (b) Donors: Igor Kononenko,
                     University E.Kardelj
                     Faculty for electrical engineering
                     Trzaska 25
                     61000 Ljubljana (tel.: (38)(+61) 265-161

                     Bojan Cestnik
                     Jozef Stefan Institute
                     Jamova 39
                     61000 Ljubljana
                     Yugoslavia (tel.: (38)(+61) 214-399 ext.287)
         (c) Date: November 1988

    3. Past Usage: (sveral)
        1. 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: 44% accuracy
        2. Clark,P. & Niblett,T. (1987). Induction in Noisy Domains.  In
           I.Bratko & N.Lavrac (Eds.) Progress in Machine Learning, 11-30,
           Sigma Press.
           -- Simple Bayes: 48% accuracy
           -- CN2 (95% threshold): 45%
        3. Michalski,R., Mozetic,I. Hong,J., & Lavrac,N. (1986).  The Multi-Purpose
           Incremental Learning System AQ15 and its Testing Applications to Three
           Medical Domains.  In Proceedings of the Fifth National Conference on
           Artificial Intelligence, 1041-1045. Philadelphia, PA: Morgan Kaufmann.
           -- Experts: 42% accuracy
           -- AQ15: 29-41%

    4. Relevant Information:
         This is one of three domains provided by the Oncology Institute
         that has repeatedly appeared in the machine learning literature.
         (See also breast-cancer and lymphography.)

    5. Number of Instances: 339

    6. Number of Attributes: 18 including the class attribute

    7. Attribute Information: (class is location of tumor)
        --- NOTE: All attribute values in the database have been entered as
                  numeric values corresponding to their index in the list
                  of attribute values for that attribute domain as given below.
        1. class: lung, head & neck, esophasus, thyroid, stomach, duoden & sm.int,
                  colon, rectum, anus, salivary glands, pancreas, gallblader,
                  liver, kidney, bladder, testis, prostate, ovary, corpus uteri,
                  cervix uteri, vagina, breast
        2. age:   <30, 30-59, >=60
        3. sex:   male, female
        4. histologic-type: epidermoid, adeno, anaplastic
        5. degree-of-diffe: well, fairly, poorly
        6. bone: yes, no
        7. bone-marrow: yes, no
        8. lung: yes, no
        9. pleura: yes, no
       10. peritoneum: yes, no
       11. liver: yes, no
       12. brain: yes, no
       13. skin: yes, no
       14. neck: yes, no
       15. supraclavicular: yes, no
       16. axillar: yes, no
       17. mediastinum: yes, no
       18. abdominal: yes, no

    8. Missing Attribute Values: (? indicates unknown value)
        Attribute#: Number of missing values
        1: 0
        2: 0
        3: 1
        4: 67
        5: 155
        6: 0
        7: 0
        8: 0
        9: 0
        10: 0
        11: 0
        12: 0
        13: 1
        14: 0
        15: 0
        16: 1
        17: 0
        18: 0

    9. Class Distribution:
        Class Index:   Number of instances in class:
                  1:   84
                  2:   20
                  3:   9
                  4:   14
                  5:   39
                  6:   1
                  7:   14
                  8:   6
                  9:   0
    	     10:   2
    	     11:   28
    	     12:   16
    	     13:   7
    	     14:   24
    	     15:   2
    	     16:   1
    	     17:   10
    	     18:   29
    	     19:   6
    	     20:   2
    	     21:   1
    	     22:   24