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thyroid-allrep

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Publicly available Visibility: public Uploaded 26-07-2016 by Rafael G. Mantovani

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General Description of Thyroid Disease Databases
and Related Files
This directory contains 6 databases, corresponding test set, and
corresponding documentation. They were left at the University of
California at Irvine by Ross Quinlan during his visit in 1987 for
the 1987 Machine Learning Workshop.
The documentation files (with file extension "names") are formatted to
be read by Quinlan's C4 decision tree program. Though briefer than
the other documentation files found in this database repository, they
should suffice to describe the database, specifically:
1. Source
2. Number and names of attributes (including class names)
3. Types of values that each attribute takes
In general, these databases are quite similar and can be characterized
somewhat as follows:
1. Many attributes (29 or so, mostly the same set over all the databases)
2. mostly numeric or Boolean valued attributes
3. thyroid disease domains (records provided by the Garavan Institute
of Sydney, Australia)
4. several missing attribute values (signified by "?")
5. small number of classes (under 10, changes with each database)
7. 2800 instances in each data set
8. 972 instances in each test set (It seems that the test sets' instances
are disjoint with respect to the corresponding data sets, but this has
not been verified)
See the following for a discussion of relevant experiments and related work:
Quinlan,J.R., Compton,P.J., Horn,K.A., & Lazurus,L. (1986).
Inductive knowledge acquisition: A case study.
In Proceedings of the Second Australian Conference on Applications
of Expert Systems. Sydney, Australia.
Quinlan,J.R. (1986). Induction of decision trees. Machine Learning,
1, 81--106.
Note that the instances in these databases are followed by a vertical
bar and a number. These appear to be a patient id number. The vertical
bar is interpreted by Quinlan's algorithms as "ignore the remainder of
this line".
======================================================================
This database now also contains an additional two data files, named
hypothyroid.data and sick-euthyroid.data. They have approximately the
same data format and set of attributes as the other 6 databases, but
their integrity is questionable. Ross Quinlan is concerned that they
may have been corrupted since they first arrived at UCI, but we have not
yet established the validity of this possibility. These 2 databases differ
in terms of their number of instances (3163) and lack of corresponding
test files. They each have 2 concepts (negative/hypothyroid and
sick-euthyroid/negative respectively). Their source also appears to
be the Garavan institute. Each contains several missing values.
Another relatively recent file thyroid0387.data has been added that
contains the latest version of an archive of thyroid diagnoses obtained
from the Garvan Institute, consisting of 9172 records from 1984 to early 1987.
A domain theory related to thyroid disease has also been added recently
(thyroid.theory).
The files new-thyroid.[names,data] were donated by Stefan Aberhard.

Class (target) | nominal | 5 unique values 0 missing | |

V1 | numeric | 94 unique values 0 missing | |

V2 | nominal | 2 unique values 0 missing | |

V3 | nominal | 2 unique values 0 missing | |

V4 | nominal | 2 unique values 0 missing | |

V5 | nominal | 2 unique values 0 missing | |

V6 | nominal | 2 unique values 0 missing | |

V7 | nominal | 2 unique values 0 missing | |

V8 | nominal | 2 unique values 0 missing | |

V9 | nominal | 2 unique values 0 missing | |

V10 | nominal | 2 unique values 0 missing | |

V11 | nominal | 2 unique values 0 missing | |

V12 | nominal | 2 unique values 0 missing | |

V13 | nominal | 2 unique values 0 missing | |

V14 | nominal | 2 unique values 0 missing | |

V15 | nominal | 2 unique values 0 missing | |

V16 | nominal | 2 unique values 0 missing | |

V17 | nominal | 2 unique values 0 missing | |

V18 | numeric | 264 unique values 0 missing | |

V19 | nominal | 2 unique values 0 missing | |

V20 | numeric | 65 unique values 0 missing | |

V21 | nominal | 2 unique values 0 missing | |

V22 | numeric | 218 unique values 0 missing | |

V23 | nominal | 2 unique values 0 missing | |

V24 | numeric | 139 unique values 0 missing | |

V25 | nominal | 2 unique values 0 missing | |

V26 | numeric | 210 unique values 0 missing |

0.65

Standard deviation of the number of distinct values among attributes of the nominal type.

0

First quartile of mutual information between the nominal attributes and the target attribute.

1.36

First quartile of skewness among attributes of the numeric type.

0.03

Average mutual information between the nominal attributes and the target attribute.

0.6

First quartile of standard deviation of attributes of the numeric type.

8.47

An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.

2.14

Average number of distinct values among the attributes of the nominal type.

11.74

Second quartile (Median) of kurtosis among attributes of the numeric type.

48.56

Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.

28.26

Second quartile (Median) of means among attributes of the numeric type.

0.02

Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

1.73

Second quartile (Median) of skewness among attributes of the numeric type.

20.39

Second quartile (Median) of standard deviation of attributes of the numeric type.

0

Minimal mutual information between the nominal attributes and the target attribute.

118.84

Third quartile of kurtosis among attributes of the numeric type.

0.12

Maximum mutual information between the nominal attributes and the target attribute.

2

The minimal number of distinct values among attributes of the nominal type.

5

The maximum number of distinct values among attributes of the nominal type.

0.04

Third quartile of mutual information between the nominal attributes and the target attribute.

5.81

Third quartile of skewness among attributes of the numeric type.

7.02

First quartile of kurtosis among attributes of the numeric type.

31.88

Third quartile of standard deviation of attributes of the numeric type.