Tic Tac Toe Endgame

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Dataset Files

Each file has a stable URL (r-link) that you can use directly in scripts, apps, or AI agents. These URLs are permanent and safe to hardcode.

/core/tic-tac-toe/

├ README.md

https://datahub.io/core/tic-tac-toe/_r/-/README.md

├ UPDATE_SCRIPT_MAINTENANCE_REPORT.md

https://datahub.io/core/tic-tac-toe/_r/-/UPDATE_SCRIPT_MAINTENANCE_REPORT.md

├ data/tic-tac-toe.csv

https://datahub.io/core/tic-tac-toe/_r/-/data/tic-tac-toe.csv

└ datapackage.json

https://datahub.io/core/tic-tac-toe/_r/-/datapackage.json

Key Files

Start with these files — they give you everything you need to understand and access the dataset.

datapackage.json— metadata & schema

https://datahub.io/core/tic-tac-toe/_r/-/datapackage.json

README.md— documentation

https://datahub.io/core/tic-tac-toe/_r/-/README.md

Typical Usage

1. Fetch datapackage.json to inspect schema and resources
2. Download data resources listed in datapackage.json
3. Read README.md for full context

Data Files

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tic-tac-toe

Field	Type	Format
TL	string	default
TM	string	default
TR	string	default
ML	string	default
MM	string	default
MR	string	default
BL	string	default
BM	string	default
BR	string	default
class	boolean	default

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About

Last updated: 9 February 2026
Total rows: ...
Format: CSV
File size: 22.4 kB
Source: [UCI - Tic-Tac-Toe Endgame Data set

About this dataset

This dataset contains tic-tac-toe endgame snapshots. First nine attributes are representing nine fields on tic-tac-toe board and tenth is class attribute which contains information if x player won.

Data

This dataset was found on UCI - Tic-Tac-Toe Endgame Data set

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.

Attribute information

TL : top left square {x,o,b}
TM : top middle square {x,o,b}
TR : top right square {x,o,b}
ML : middle left square {x,o,b}
MM : middle middle square {x,o,b}
MR : middle right square {x,o,b}
BL : bottom left square {x,o,b}
BM : bottom middle square {x,o,b}
BR : bottom right square {x,o,b}
class :
- true: x won
- false: x lost

Values are:

x : x player
o : o player
b : blank field

Data is located in directory data

data/hepatitis.csv

Preparation

This script should be run using Python 3.

Scripts are in directory scripts

scripts/main.py

License

Licensed under the Public Domain Dedication and Licence (assuming either no rights or public domain licence in source data).