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satellite_image

satellite_image

deactivated ARFF Publicly available Visibility: public Uploaded 04-05-2017 by Rafael Gomes Mantovani
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Target feature converted to categorical.

37 features

Class (target)nominal6 unique values
0 missing
attr1numeric51 unique values
0 missing
attr2numeric84 unique values
0 missing
attr3numeric76 unique values
0 missing
attr4numeric102 unique values
0 missing
attr5numeric51 unique values
0 missing
attr6numeric82 unique values
0 missing
attr7numeric76 unique values
0 missing
attr8numeric103 unique values
0 missing
attr9numeric50 unique values
0 missing
attr10numeric81 unique values
0 missing
attr11numeric78 unique values
0 missing
attr12numeric104 unique values
0 missing
attr13numeric51 unique values
0 missing
attr14numeric83 unique values
0 missing
attr15numeric78 unique values
0 missing
attr16numeric101 unique values
0 missing
attr17numeric50 unique values
0 missing
attr18numeric80 unique values
0 missing
attr19numeric77 unique values
0 missing
attr20numeric104 unique values
0 missing
attr21numeric50 unique values
0 missing
attr22numeric80 unique values
0 missing
attr23numeric78 unique values
0 missing
attr24numeric104 unique values
0 missing
attr25numeric51 unique values
0 missing
attr26numeric82 unique values
0 missing
attr27numeric75 unique values
0 missing
attr28numeric102 unique values
0 missing
attr29numeric50 unique values
0 missing
attr30numeric81 unique values
0 missing
attr31numeric77 unique values
0 missing
attr32numeric103 unique values
0 missing
attr33numeric50 unique values
0 missing
attr34numeric80 unique values
0 missing
attr35numeric77 unique values
0 missing
attr36numeric104 unique values
0 missing

62 properties

6435
Number of instances (rows) of the dataset.
37
Number of attributes (columns) of the dataset.
6
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.
2.48
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.
0.01
Number of attributes divided by the number of instances.
6
Average number of distinct values among the attributes of the nominal type.
-0.48
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.
0.04
Mean skewness among attributes of the numeric type.
82.76
Second quartile (Median) of means among attributes of the numeric type.
23.82
Percentage of instances belonging to the most frequent class.
18.01
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
1533
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
-0.04
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-0.92
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
17.81
Second quartile (Median) of standard deviation of attributes of the numeric type.
1.28
Maximum kurtosis among attributes of the numeric type.
68.73
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
99.31
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.
0.85
Third quartile of kurtosis among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
6
The minimal number of distinct values among attributes of the nominal type.
97.3
Percentage of numeric attributes.
95.04
Third quartile of means among attributes of the numeric type.
6
The maximum number of distinct values among attributes of the nominal type.
-0.67
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.
0.92
Maximum skewness among attributes of the numeric type.
13.4
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.67
Third quartile of skewness among attributes of the numeric type.
22.91
Maximum standard deviation of attributes of the numeric type.
9.73
Percentage of instances belonging to the least frequent class.
-0.84
First quartile of kurtosis among attributes of the numeric type.
21.87
Third quartile of standard deviation of attributes of the numeric type.
Average entropy of the attributes.
626
Number of instances belonging to the least frequent class.
72.65
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.
83.47
Mean of means among attributes of the numeric type.
-0.52
First quartile of skewness among attributes of the numeric type.
0.85
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
14.36
First quartile of standard deviation of attributes of the numeric type.

12 tasks

1 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
0 runs - estimation_procedure: 10-fold Crossvalidation - 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 - 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
Define a new task