Chess (King-Rook vs. King-Pawn)
Donated on 7/31/1989
King+Rook versus King+Pawn on a7 (usually abbreviated KRKPA7).
Dataset Characteristics
Multivariate
Subject Area
Games
Associated Tasks
Classification
Feature Type
Categorical
# Instances
3196
# Features
35
Dataset Information
Additional Information
The dataset format is described below. Note: the format of this database was modified on 2/26/90 to conform with the format of all the other databases in the UCI repository of machine learning databases.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| bkblk | Feature | Categorical | no | ||
| bknwy | Feature | Categorical | no | ||
| bkon8 | Feature | Categorical | no | ||
| bkona | Feature | Categorical | no | ||
| bkspr | Feature | Categorical | no | ||
| bkxbq | Feature | Categorical | no | ||
| bkxcr | Feature | Categorical | no | ||
| bkxwp | Feature | Categorical | no | ||
| blxwp | Feature | Categorical | no | ||
| bxqsq | Feature | Categorical | no |
0 to 10 of 36
Additional Variable Information
Attributes: see Shapiro's book.
Class Labels
Classes (2): -- White-can-win ("won") and White-cannot-win ("nowin"). I believe that White is deemed to be unable to win if the Black pawn can safely advance.
Dataset Files
| File | Size |
|---|---|
| kr-vs-kp.data | 240.2 KB |
| kr-vs-kp.names | 2.9 KB |
| Index | 131 Bytes |
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset chess_king_rook_vs_king_pawn = fetch_ucirepo(id=22) # data (as pandas dataframes) X = chess_king_rook_vs_king_pawn.data.features y = chess_king_rook_vs_king_pawn.data.targets # metadata print(chess_king_rook_vs_king_pawn.metadata) # variable information print(chess_king_rook_vs_king_pawn.variables)
Shapiro, A. (1983). Chess (King-Rook vs. King-Pawn) [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5DK5C.
Keywords
Creators
Alen Shapiro
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.