Tic-Tac-Toe Endgame
Donated on 8/18/1991
Binary classification task on possible configurations of tic-tac-toe game
Dataset Characteristics
Multivariate
Subject Area
Games
Associated Tasks
Classification
Feature Type
Categorical
# Instances
958
# Features
9
Dataset Information
Additional Information
This database encodes the complete set of possible board configurations at the end of tic-tac-toe games, where "x" is assumed to have played first. The target concept is "win for x" (i.e., true when "x" has one of 8 possible ways to create a "three-in-a-row"). Interestingly, this raw database gives a stripped-down decision tree algorithm (e.g., ID3) fits. However, the rule-based CN2 algorithm, the simple IB1 instance-based learning algorithm, and the CITRE feature-constructing decision tree algorithm perform well on it.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| class | Target | Categorical | no | ||
| top-left-square | Feature | Categorical | no | ||
| top-middle-square | Feature | Categorical | no | ||
| top-right-square | Feature | Categorical | no | ||
| middle-left-square | Feature | Categorical | no | ||
| middle-middle-square | Feature | Categorical | no | ||
| middle-right-square | Feature | Categorical | no | ||
| bottom-left-square | Feature | Categorical | no | ||
| bottom-middle-square | Feature | Categorical | no | ||
| bottom-right-square | Feature | Categorical | no |
0 to 10 of 10
Additional Variable Information
1. top-left-square: {x,o,b} 2. top-middle-square: {x,o,b} 3. top-right-square: {x,o,b} 4. middle-left-square: {x,o,b} 5. middle-middle-square: {x,o,b} 6. middle-right-square: {x,o,b} 7. bottom-left-square: {x,o,b} 8. bottom-middle-square: {x,o,b} 9. bottom-right-square: {x,o,b} 10. Class: {positive,negative}
Baseline Model Performance
Papers Citing this Dataset
By Benjamin Letham, Cynthia Rudin, Tyler McCormick, David Madigan. 2015
Published in Annals of Applied Statistics 2015, Vol. 9, No. 3, 1350-1371.
By Mahawaga Chamikara, Akalanka Galappaththi, Roshan Yapa, Ruwan Nawarathna, Saluka Kodituwakku, Jagath Gunatilake, Aththanapola Jayathilake, Liwan Liyanage. 2015
Published in PeerJ PrePrints.
By Fan Min, Qinghua Hu, William Zhu. 2012
Published in ArXiv.
By Frédéric Tantini, Alain Terlutte, Fabien Torre. 2010
Published in ICGI.
0 to 4 of 4
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset tic_tac_toe_endgame = fetch_ucirepo(id=101) # data (as pandas dataframes) X = tic_tac_toe_endgame.data.features y = tic_tac_toe_endgame.data.targets # metadata print(tic_tac_toe_endgame.metadata) # variable information print(tic_tac_toe_endgame.variables)
Aha,David. (1991). Tic-Tac-Toe Endgame. UCI Machine Learning Repository. https://doi.org/10.24432/C5688J.
@misc{misc_tic-tac-toe_endgame_101,
author = {Aha,David},
title = {{Tic-Tac-Toe Endgame}},
year = {1991},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5688J}
}Creators
David Aha
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.