Data
connect-4

connect-4

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  • OpenML-CC18 OpenML100 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

62 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.
0.03
Maximum mutual information between the nominal attributes and the target attribute.
3
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of numeric attributes.
Third quartile of means among attributes of the numeric type.
3
The maximum number of distinct values among attributes of the nominal type.
Minimum skewness among attributes of the numeric type.
100
Percentage of nominal attributes.
0.01
Third quartile of mutual information between the nominal attributes and the target attribute.
Maximum skewness among attributes of the numeric type.
Minimum standard deviation of attributes of the numeric type.
0.16
First quartile of entropy among attributes.
Third quartile of skewness among attributes of the numeric type.
Maximum standard deviation of attributes of the numeric type.
9.55
Percentage of instances belonging to the least frequent class.
First quartile of kurtosis among attributes of the numeric type.
Third quartile of standard deviation of attributes of the numeric type.
0.68
Average entropy of the attributes.
6449
Number of instances belonging to the least frequent class.
First quartile of means among attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
0
First quartile of mutual information between the nominal attributes and the target attribute.
Mean of means among attributes of the numeric type.
First quartile of skewness among attributes of the numeric type.
0.01
Average mutual information between the nominal attributes and the target attribute.
First quartile of standard deviation of attributes of the numeric type.
0.62
Average class difference between consecutive instances.
113.88
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0.56
Second quartile (Median) of entropy among attributes.
1.22
Entropy of the target attribute values.
3
Average number of distinct values among the attributes of the nominal type.
Second quartile (Median) of kurtosis among attributes of the numeric type.
0
Number of attributes divided by the number of instances.
205.84
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
Mean skewness among attributes of the numeric type.
Second quartile (Median) of means among attributes of the numeric type.
65.83
Percentage of instances belonging to the most frequent class.
Mean standard deviation of attributes of the numeric type.
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
44473
Number of instances belonging to the most frequent class.
0.01
Minimal entropy among attributes.
Second quartile (Median) of skewness among attributes of the numeric type.
1.58
Maximum entropy among attributes.
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum kurtosis among attributes of the numeric type.
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
1.22
Third quartile of entropy among attributes.
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
Third quartile of kurtosis among attributes of the numeric type.

15 tasks

9235 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - 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 - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
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