Data
connect-4

connect-4

active ARFF public Visibility: public Uploaded 06-04-2017 by Pieter Gijsbers
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  • Games OpenML-CC18 OpenML100 Recreation Strategy study_123 study_135 study_14 study_218 study_99 uci
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Author: John Tromp Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Connect-4) - 1995 Please cite: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) Connect-4 This database contains all legal 8-ply positions in the game of connect-4 in which neither player has won yet, and in which the next move is not forced. Attributes represent board positions on a 6x6 board. The outcome class is the game-theoretical value for the first player (2: win, 1: loss, 0: draw). ### Attribute Information The board is numbered like: 6 . . . . . . . 5 . . . . . . . 4 . . . . . . . 3 . . . . . . . 2 . . . . . . . 1 . . . . . . . a b c d e f g The values represent: 0: Blank 1: Taken by Player 1 2: Taken by Player 2

43 features

class (target)nominal3 unique values
0 missing
a1nominal3 unique values
0 missing
a2nominal3 unique values
0 missing
a3nominal3 unique values
0 missing
a4nominal3 unique values
0 missing
a5nominal3 unique values
0 missing
a6nominal3 unique values
0 missing
b1nominal3 unique values
0 missing
b2nominal3 unique values
0 missing
b3nominal3 unique values
0 missing
b4nominal3 unique values
0 missing
b5nominal3 unique values
0 missing
b6nominal3 unique values
0 missing
c1nominal3 unique values
0 missing
c2nominal3 unique values
0 missing
c3nominal3 unique values
0 missing
c4nominal3 unique values
0 missing
c5nominal3 unique values
0 missing
c6nominal3 unique values
0 missing
d1nominal3 unique values
0 missing
d2nominal3 unique values
0 missing
d3nominal3 unique values
0 missing
d4nominal3 unique values
0 missing
d5nominal3 unique values
0 missing
d6nominal3 unique values
0 missing
e1nominal3 unique values
0 missing
e2nominal3 unique values
0 missing
e3nominal3 unique values
0 missing
e4nominal3 unique values
0 missing
e5nominal3 unique values
0 missing
e6nominal3 unique values
0 missing
f1nominal3 unique values
0 missing
f2nominal3 unique values
0 missing
f3nominal3 unique values
0 missing
f4nominal3 unique values
0 missing
f5nominal3 unique values
0 missing
f6nominal3 unique values
0 missing
g1nominal3 unique values
0 missing
g2nominal3 unique values
0 missing
g3nominal3 unique values
0 missing
g4nominal3 unique values
0 missing
g5nominal3 unique values
0 missing
g6nominal3 unique values
0 missing

19 properties

67557
Number of instances (rows) of the dataset.
43
Number of attributes (columns) of the dataset.
3
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
0
Number of numeric attributes.
43
Number of nominal attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
0.62
Average class difference between consecutive instances.
0
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
100
Percentage of nominal attributes.
65.83
Percentage of instances belonging to the most frequent class.
44473
Number of instances belonging to the most frequent class.
9.55
Percentage of instances belonging to the least frequent class.
6449
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

30 tasks

9763 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
2 runs - estimation_procedure: 33% Holdout set - target_feature: class
1 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 4-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: classification problem
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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