openml-datasets

name	type	format
bkblk	string	default
bknwy	string	default
bkon8	string	default
bkona	string	default
bkspr	string	default
bkxbq	string	default
bkxcr	string	default
bkxwp	string	default
blxwp	string	default
bxqsq	string	default
cntxt	string	default
dsopp	string	default
dwipd	string	default
hdchk	string	default
katri	string	default
mulch	string	default
qxmsq	string	default
r2ar8	string	default
reskd	string	default
reskr	string	default
rimmx	string	default
rkxwp	string	default
rxmsq	string	default
simpl	string	default
skach	string	default
skewr	string	default
skrxp	string	default
spcop	string	default
stlmt	string	default
thrsk	string	default
wkcti	string	default
wkna8	string	default
wknck	string	default
wkovl	string	default
wkpos	string	default
wtoeg	string	default
class	string	default

Data Files

File	Description	Size	Last modified	Download
kr-vs-kp		490 kB	3 months ago	kr-vs-kp
kr-vs-kp		483 kB	3 months ago	kr-vs-kp

Files	Size	Format	Created	Updated	License	Source
2	973 kB	arff, csv		about 2 months ago	Open Data Commons Public Domain Dedication and License

The resources for this dataset can be found at https://www.openml.org/d/3

Author: Alen Shapiro Source: UCI
Please cite: UCI citation policy

Title: Chess End-Game – King+Rook versus King+Pawn on a7 (usually abbreviated KRKPA7). The pawn on a7 means it is one square away from queening. It is the King+Rook's side (white) to move.
Sources: (a) Database originally generated and described by Alen Shapiro. (b) Donor/Coder: Rob Holte (holte@uottawa.bitnet). The database was supplied to Holte by Peter Clark of the Turing Institute in Glasgow (pete@turing.ac.uk). (c) Date: 1 August 1989
Past Usage:
- Alen D. Shapiro (1983,1987), "Structured Induction in Expert Systems", Addison-Wesley. This book is based on Shapiro's Ph.D. thesis (1983) at the University of Edinburgh entitled "The Role of Structured Induction in Expert Systems".
- Stephen Muggleton (1987), "Structuring Knowledge by Asking Questions", pp.218-229 in "Progress in Machine Learning", edited by I. Bratko and Nada Lavrac, Sigma Press, Wilmslow, England SK9 5BB.
- Robert C. Holte, Liane Acker, and Bruce W. Porter (1989), "Concept Learning and the Problem of Small Disjuncts", Proceedings of IJCAI. Also available as technical report AI89-106, Computer Sciences Department, University of Texas at Austin, Austin, Texas 78712.
Relevant 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.
Number of Instances: 3196 total
Number of Attributes: 36
Attribute Summaries: 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. Attributes: see Shapiro's book.
Missing Attributes: – none
Class Distribution: In 1669 of the positions (52%), White can win. In 1527 of the positions (48%), White cannot win.

The format for instances in this database is a sequence of 37 attribute values. Each instance is a board-descriptions for this chess endgame. The first 36 attributes describe the board. The last (37th) attribute is the classification: "win" or "nowin". There are 0 missing values. A typical board-description is

f,f,f,f,f,f,f,f,f,f,f,f,l,f,n,f,f,t,f,f,f,f,f,f,f,t,f,f,f,f,f,f,f,t,t,n,won

The names of the features do not appear in the board-descriptions. Instead, each feature correponds to a particular position in the feature-value list. For example, the head of this list is the value for the feature "bkblk". The following is the list of features, in the order in which their values appear in the feature-value list:

[bkblk,bknwy,bkon8,bkona,bkspr,bkxbq,bkxcr,bkxwp,blxwp,bxqsq,cntxt,dsopp,dwipd, hdchk,katri,mulch,qxmsq,r2ar8,reskd,reskr,rimmx,rkxwp,rxmsq,simpl,skach,skewr, skrxp,spcop,stlmt,thrsk,wkcti,wkna8,wknck,wkovl,wkpos,wtoeg]

In the file, there is one instance (board position) per line.

Num Instances: 3196 Num Attributes: 37 Num Continuous: 0 (Int 0 / Real 0) Num Discrete: 37 Missing values: 0 / 0.0%

name 1 'bkblk' 2 'bknwy' 3 'bkon8' 4 'bkona' 5 'bkspr' 6 'bkxbq' 7 'bkxcr' 8 'bkxwp' 9 'blxwp' 10 'bxqsq' 11 'cntxt' 12 'dsopp' 13 'dwipd' 14 'hdchk' 15 'katri' 16 'mulch' 17 'qxmsq' 18 'r2ar8' 19 'reskd' 20 'reskr' 21 'rimmx' 22 'rkxwp' 23 'rxmsq' 24 'simpl' 25 'skach' 26 'skewr' 27 'skrxp' 28 'spcop' 29 'stlmt' 30 'thrsk' 31 'wkcti' 32 'wkna8' 33 'wknck' 34 'wkovl' 35 'wkpos' 36 'wtoeg' 37 'class' type enum ints real missing distinct (1) Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 3 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0% Enum 100% 0% 0% 0 / 0% 2 / 0% 0%