Hayes-Roth
Donated on 2/28/1989
Topic: human subjects study
Dataset Characteristics
Multivariate
Subject Area
Social Science
Associated Tasks
Classification
Feature Type
Categorical
# Instances
160
# Features
4
Dataset Information
Additional Information
This database contains 5 numeric-valued attributes. Only a subset of 3 are used during testing (the latter 3). Furthermore, only 2 of the 3 concepts are "used" during testing (i.e., those with the prototypes 000 and 111). I've mapped all values to their zero-indexing equivalents. Some instances could be placed in either category 0 or 1. I've followed the authors' suggestion, placing them in each category with equal probability. I've replaced the actual values of the attributes (i.e., hobby has values chess, sports and stamps) with numeric values. I think this is how the authors' did this when testing the categorization models described in the paper. I find this unfair. While the subjects were able to bring background knowledge to bear on the attribute values and their relationships, the algorithms were provided with no such knowledge. I'm uncertain whether the 2 distractor attributes (name and hobby) are presented to the authors' algorithms during testing. However, it is clear that only the age, educational status, and marital status attributes are given during the human subjects' transfer tests.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Demographic | Description | Units | Missing Values |
|---|---|---|---|---|---|---|
| name | ID | Integer | no | |||
| hobby | Feature | Integer | no | |||
| age | Feature | Integer | Age | no | ||
| educational level | Feature | Integer | Education Level | no | ||
| marital status | Feature | Integer | Marital Status | no | ||
| class | Target | Categorical | no |
0 to 6 of 6
Additional Variable Information
-- 1. name: distinct for each instance and represented numerically -- 2. hobby: nominal values ranging between 1 and 3 -- 3. age: nominal values ranging between 1 and 4 -- 4. educational level: nominal values ranging between 1 and 4 -- 5. marital status: nominal values ranging between 1 and 4 -- 6. class: nominal value between 1 and 3
Dataset Files
| File | Size |
|---|---|
| hayes-roth.names | 6.3 KB |
| hayes-roth.data | 1.7 KB |
| hayes-roth.test | 280 Bytes |
| Index | 160 Bytes |
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset hayes_roth = fetch_ucirepo(id=44) # data (as pandas dataframes) X = hayes_roth.data.features y = hayes_roth.data.targets # metadata print(hayes_roth.metadata) # variable information print(hayes_roth.variables)
Hayes-Roth, B. & Hayes-Roth, F. (1977). Hayes-Roth [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5501T.
Creators
Barbara Hayes-Roth
Frederick Hayes-Roth
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.