Data
BNG(SPECTF)

BNG(SPECTF)

active ARFF public domain Visibility: public Uploaded 12-11-2014 by Jan van Rijn
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45 features

OVERALL_DIAGNOSIS (target)nominal2 unique values
0 missing
F1Rnumeric976730 unique values
0 missing
F1Snumeric980823 unique values
0 missing
F2Rnumeric973430 unique values
0 missing
F2Snumeric974746 unique values
0 missing
F3Rnumeric975938 unique values
0 missing
F3Snumeric976843 unique values
0 missing
F4Rnumeric967517 unique values
0 missing
F4Snumeric974088 unique values
0 missing
F5Rnumeric973057 unique values
0 missing
F5Snumeric978013 unique values
0 missing
F6Rnumeric968475 unique values
0 missing
F6Snumeric973309 unique values
0 missing
F7Rnumeric970017 unique values
0 missing
F7Snumeric973109 unique values
0 missing
F8Rnumeric978620 unique values
0 missing
F8Snumeric978202 unique values
0 missing
F9Rnumeric971014 unique values
0 missing
F9Snumeric971883 unique values
0 missing
F10Rnumeric977956 unique values
0 missing
F10Snumeric977447 unique values
0 missing
F11Rnumeric967396 unique values
0 missing
F11Snumeric973969 unique values
0 missing
F12Rnumeric977107 unique values
0 missing
F12Snumeric978342 unique values
0 missing
F13Rnumeric983315 unique values
0 missing
F13Snumeric985609 unique values
0 missing
F14Rnumeric977958 unique values
0 missing
F14Snumeric979709 unique values
0 missing
F15Rnumeric975661 unique values
0 missing
F15Snumeric974867 unique values
0 missing
F16Rnumeric958626 unique values
0 missing
F16Snumeric961585 unique values
0 missing
F17Rnumeric967567 unique values
0 missing
F17Snumeric966637 unique values
0 missing
F18Rnumeric966233 unique values
0 missing
F18Snumeric969224 unique values
0 missing
F19Rnumeric975683 unique values
0 missing
F19Snumeric977706 unique values
0 missing
F20Rnumeric976202 unique values
0 missing
F20Snumeric980216 unique values
0 missing
F21Rnumeric980162 unique values
0 missing
F21Snumeric981439 unique values
0 missing
F22Rnumeric981955 unique values
0 missing
F22Snumeric984111 unique values
0 missing

62 properties

1000000
Number of instances (rows) of the dataset.
45
Number of attributes (columns) of the dataset.
2
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.
44
Number of numeric attributes.
1
Number of nominal attributes.
2.22
Percentage of binary attributes.
8.84
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
0.54
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
4.87
Maximum kurtosis among attributes of the numeric type.
51.69
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
3.22
Third quartile of kurtosis among attributes of the numeric type.
73.67
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
97.78
Percentage of numeric attributes.
67.92
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
2.22
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2
The maximum number of distinct values among attributes of the nominal type.
-2.13
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
-1.11
Third quartile of skewness among attributes of the numeric type.
-0.7
Maximum skewness among attributes of the numeric type.
5.81
Minimum standard deviation of attributes of the numeric type.
1.22
First quartile of kurtosis among attributes of the numeric type.
10.52
Third quartile of standard deviation of attributes of the numeric type.
14.15
Maximum standard deviation of attributes of the numeric type.
28.13
Percentage of instances belonging to the least frequent class.
62.12
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.
Average entropy of the attributes.
281300
Number of instances belonging to the least frequent class.
First quartile of mutual information between the nominal attributes and the target attribute.
2.33
Mean kurtosis among attributes of the numeric type.
1
Number of binary attributes.
-1.76
First quartile of skewness among attributes of the numeric type.
65.13
Mean of means among attributes of the numeric type.
7.8
First quartile of standard deviation of attributes of the numeric type.
0.6
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among attributes.
0.86
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.
2.07
Second quartile (Median) of kurtosis among attributes of the numeric type.
0
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
65.22
Second quartile (Median) of means 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.
-1.42
Mean skewness among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
71.87
Percentage of instances belonging to the most frequent class.
9.21
Mean standard deviation of attributes of the numeric type.
-1.41
Second quartile (Median) of skewness among attributes of the numeric type.
718700
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.

4 tasks

0 runs - estimation_procedure: 33% Holdout set - target_feature: OVERALL_DIAGNOSIS
47 runs - estimation_procedure: Interleaved Test then Train - target_feature: OVERALL_DIAGNOSIS
0 runs - estimation_procedure: 50 times Clustering
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