Data
poker

poker

active Sparse_ARFF Publicly available Visibility: public Uploaded 18-06-2015 by Farooq Zuberi
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Author: UC Irvine Machine Learning Repository libSVM","AAD group Source: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass.html) - Date unknown Please cite: #Dataset from the LIBSVM data repository.

11 features

class (target)numeric10 unique values
0 missing
att_1numeric4 unique values
0 missing
att_2numeric13 unique values
0 missing
att_3numeric4 unique values
0 missing
att_4numeric13 unique values
0 missing
att_5numeric4 unique values
0 missing
att_6numeric13 unique values
0 missing
att_7numeric4 unique values
0 missing
att_8numeric13 unique values
0 missing
att_9numeric4 unique values
0 missing
att_10numeric13 unique values
0 missing

62 properties

1025010
Number of instances (rows) of the dataset.
11
Number of attributes (columns) of the dataset.
0
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.
11
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
-1.22
Second quartile (Median) of kurtosis among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
0.18
Mean skewness among attributes of the numeric type.
2.5
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
2.28
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
-0
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.36
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
1.12
Second quartile (Median) of standard deviation of attributes of the numeric type.
7.74
Maximum kurtosis among attributes of the numeric type.
0.62
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
7.01
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
-1.21
Third quartile of kurtosis among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
100
Percentage of numeric attributes.
7
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-0
Minimum skewness among attributes of the numeric type.
0
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2.01
Maximum skewness among attributes of the numeric type.
0.77
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0
Third quartile of skewness among attributes of the numeric type.
3.74
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.36
First quartile of kurtosis among attributes of the numeric type.
3.74
Third quartile of standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
2.5
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
-0.47
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
4.37
Mean of means among attributes of the numeric type.
-0
First quartile of skewness among attributes of the numeric type.
0.28
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
1.12
First quartile of standard deviation of attributes of the numeric type.
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Second quartile (Median) of entropy among attributes.

5 tasks

1 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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