This section describes main characteristics of the hayes-roth data set and its attributes:
General information
Hayes-Roth data set |
Type | Classification | Origin | Laboratory |
Features | 4 | (Real / Integer / Nominal) | (0 / 4 / 0) |
Instances | 160 |
Classes | 3 |
Missing values? | No |
Attribute description
Attribute | Domain |
Hobby | [1, 3] |
Age | [1, 4] |
EducationalLevel | [1, 4] |
MaritalStatus | [1, 4] |
Class | {1,2,3} |
Additional information
An artificial data set created to test the behaviour of prototype-based classifiers. The hobby attribute was generated at random, thus it is employed to add noise to the data. This is a modification of the original UCI data set, where attribute name has been deleted, due to it only provided to the train data in the original source.
In this section you can download some files related to the hayes-roth data set:
- The complete data set already formatted in KEEL format can be downloaded from
here.
- A copy of the data set already partitioned by means of a 10-folds cross validation procedure can be downloaded from here.
- A copy of the data set already partitioned by means of a 5-folds cross validation procedure can be downloaded from here.
- The header file associated to this data set can be downloaded from here.
- This is not a native data set from the KEEL project. It has been obtained from the UCI Machine Learning repository. The original page where the data set can be found is: http://archive.ics.uci.edu/ml/datasets/Hayes-Roth.
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