Data
Mine

Mine

active ARFF Public Domain (CC0) Visibility: public Uploaded 16-11-2019 by Ahmed Alaff
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dataset for feature extraction

37 features

attribute_0numeric66 unique values
0 missing
attribute_1numeric66 unique values
0 missing
attribute_2numeric66 unique values
0 missing
attribute_3numeric66 unique values
0 missing
attribute_4numeric66 unique values
0 missing
attribute_5numeric66 unique values
0 missing
attribute_6numeric66 unique values
0 missing
attribute_7numeric66 unique values
0 missing
attribute_8numeric66 unique values
0 missing
attribute_9numeric66 unique values
0 missing
attribute_10numeric66 unique values
0 missing
attribute_11numeric66 unique values
0 missing
attribute_12numeric66 unique values
0 missing
attribute_13numeric66 unique values
0 missing
attribute_14numeric66 unique values
0 missing
attribute_15numeric66 unique values
0 missing
attribute_16numeric66 unique values
0 missing
attribute_17numeric66 unique values
0 missing
attribute_18numeric66 unique values
0 missing
attribute_19numeric66 unique values
0 missing
attribute_20numeric66 unique values
0 missing
attribute_21numeric66 unique values
0 missing
attribute_22numeric66 unique values
0 missing
attribute_23numeric66 unique values
0 missing
attribute_24numeric66 unique values
0 missing
attribute_25numeric66 unique values
0 missing
attribute_26numeric66 unique values
0 missing
attribute_27numeric66 unique values
0 missing
attribute_28numeric66 unique values
0 missing
attribute_29numeric66 unique values
0 missing
attribute_30numeric66 unique values
0 missing
attribute_31numeric66 unique values
0 missing
attribute_32numeric66 unique values
0 missing
attribute_33numeric66 unique values
0 missing
attribute_34numeric66 unique values
0 missing
attribute_35numeric66 unique values
0 missing
attribute_36nominal2 unique values
0 missing

62 properties

69
Number of instances (rows) of the dataset.
37
Number of attributes (columns) of the dataset.
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.
36
Number of numeric attributes.
1
Number of nominal attributes.
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.
0.54
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
-0.51
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.
0.3
Mean skewness among attributes of the numeric type.
1.2
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
13.7
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.
0.16
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.4
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
2.58
Second quartile (Median) of standard deviation of attributes of the numeric type.
6.39
Maximum kurtosis among attributes of the numeric type.
-0.06
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
145.82
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.
0.55
Third quartile of kurtosis 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.
97.3
Percentage of numeric attributes.
93.63
Third quartile of means among attributes of the numeric type.
2
The maximum number of distinct values among attributes of the nominal type.
-1.8
Minimum skewness among attributes of the numeric type.
2.7
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2.46
Maximum skewness among attributes of the numeric type.
0.03
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.7
Third quartile of skewness among attributes of the numeric type.
53.25
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.95
First quartile of kurtosis among attributes of the numeric type.
29.97
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.
0.29
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.
0.15
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.
36.42
Mean of means among attributes of the numeric type.
-0.13
First quartile of skewness among attributes of the numeric type.
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.16
First quartile of standard deviation of attributes of the numeric type.

8 tasks

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 - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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