This section describes main characteristics of the chess data set and its attributes:
General information
Chess (KingRook vs. KingPawn) data set 
Type  Classification  Origin  Laboratory 
Features  36  (Real / Integer / Nominal)  (0 / 0 / 36) 
Instances  3196 
Classes  2 
Missing values?  No 
Attribute description
Attribute  Domain  Attribute  Domain  Attribute  Domain 
Bkblk  {f,t}  Dwipd  {l,g}  Skach  {f,t} 
Bknwy  {f,t}  Hdchk  {f,t}  Skewr  {f,t} 
Bkon8  {f,t}  Katri5  {n,w,b}  Skrxp  {f,t} 
Bkona  {f,t}  Mulch  {f,t}  Spcop  {f,t} 
Bkspr  {f,t}  Qxmsq  {f,t}  Stlmt  {f,t} 
Bkxbq  {f,t}  R2ar8  {f,t}  Thrsk  {f,t} 
Bkxcr  {f,t}  Reskd  {f,t}  Wkcti  {f,t} 
Bkxwp  {f,t}  Reskr  {f,t}  Wkna8  {f,t} 
Blxwp  {f,t}  Rimmx  {f,t}  Wknck  {f,t} 
Bxqsq  {f,t}  Rkxwp  {f,t}  Wkovl  {f,t} 
Cntxt  {f,t}  Rxmsq  {f,t}  Wkpos  {f,t} 
Dsopp  {f,t}  Simpl  {f,t}  Wtoeg  {n,t} 
Class  {won,nowin} 
Additional information
A data set representing a chees end game, where a pawn on a7 is one square away from queening. The task is to determine if White can win or not.
The description of attributes can be found in: Alen D. Shapiro (1983,1987), Structured Induction in Expert Systems, AddisonWesley.
In this section you can download some files related to the chess data set:
 The complete data set already formatted in KEEL format can be downloaded from
here.
 A copy of the data set already partitioned by means of a 10folds cross validation procedure can be downloaded from here.
 A copy of the data set already partitioned by means of a 5folds cross validation procedure can be downloaded from here.
 The header file associated to this data set can be downloaded from here.
 This is not a native data set from the KEEL project. It has been obtained from the UCI Machine Learning repository. The original page where the data set can be found is: http://archive.ics.uci.edu/ml/datasets/Chess+%28KingRook+vs.+KingPawn%29.
