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active ARFF Publicly available Visibility: public Uploaded 03-04-2019 by Quay Au
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Multi-label dataset. The image benchmark dataset consists of 2000 natural scene images. Zhou and Zhang (2007) extracted 135 features for each image and made it publicly available as processed image dataset. Each observation can be associated with different label sets, where all possible labels are {desert, mountains, sea, sunset, trees}. About 22% of the images belong to more than one class. However, images belonging to three classes or more are very rare.

140 features

desert (target)	nominal	2 unique values 0 missing
mountains (target)	nominal	2 unique values 0 missing
sea (target)	nominal	2 unique values 0 missing
sunset (target)	nominal	2 unique values 0 missing
trees (target)	nominal	2 unique values 0 missing
Feature1	numeric	808 unique values 0 missing
Feature2	numeric	821 unique values 0 missing
Feature3	numeric	809 unique values 0 missing
Feature4	numeric	780 unique values 0 missing
Feature5	numeric	792 unique values 0 missing
Feature6	numeric	790 unique values 0 missing
Feature7	numeric	788 unique values 0 missing
Feature8	numeric	788 unique values 0 missing
Feature9	numeric	782 unique values 0 missing
Feature10	numeric	704 unique values 0 missing
Feature11	numeric	706 unique values 0 missing
Feature12	numeric	717 unique values 0 missing
Feature13	numeric	684 unique values 0 missing
Feature14	numeric	681 unique values 0 missing
Feature15	numeric	678 unique values 0 missing
Feature16	numeric	677 unique values 0 missing
Feature17	numeric	701 unique values 0 missing
Feature18	numeric	686 unique values 0 missing
Feature19	numeric	804 unique values 0 missing
Feature20	numeric	811 unique values 0 missing
Feature21	numeric	793 unique values 0 missing
Feature22	numeric	765 unique values 0 missing
Feature23	numeric	764 unique values 0 missing
Feature24	numeric	763 unique values 0 missing
Feature25	numeric	705 unique values 0 missing
Feature26	numeric	731 unique values 0 missing
Feature27	numeric	722 unique values 0 missing
Feature28	numeric	632 unique values 0 missing
Feature29	numeric	633 unique values 0 missing
Feature30	numeric	615 unique values 0 missing
Feature31	numeric	626 unique values 0 missing
Feature32	numeric	640 unique values 0 missing
Feature33	numeric	631 unique values 0 missing
Feature34	numeric	610 unique values 0 missing
Feature35	numeric	629 unique values 0 missing
Feature36	numeric	600 unique values 0 missing
Feature37	numeric	581 unique values 0 missing
Feature38	numeric	587 unique values 0 missing
Feature39	numeric	574 unique values 0 missing
Feature40	numeric	593 unique values 0 missing
Feature41	numeric	603 unique values 0 missing
Feature42	numeric	557 unique values 0 missing
Feature43	numeric	554 unique values 0 missing
Feature44	numeric	573 unique values 0 missing
Feature45	numeric	550 unique values 0 missing
Feature46	numeric	570 unique values 0 missing
Feature47	numeric	558 unique values 0 missing
Feature48	numeric	545 unique values 0 missing
Feature49	numeric	565 unique values 0 missing
Feature50	numeric	566 unique values 0 missing
Feature51	numeric	515 unique values 0 missing
Feature52	numeric	533 unique values 0 missing
Feature53	numeric	533 unique values 0 missing
Feature54	numeric	493 unique values 0 missing
Feature55	numeric	846 unique values 0 missing
Feature56	numeric	852 unique values 0 missing
Feature57	numeric	861 unique values 0 missing
Feature58	numeric	865 unique values 0 missing
Feature59	numeric	879 unique values 0 missing
Feature60	numeric	887 unique values 0 missing
Feature61	numeric	852 unique values 0 missing
Feature62	numeric	853 unique values 0 missing
Feature63	numeric	860 unique values 0 missing
Feature64	numeric	784 unique values 0 missing
Feature65	numeric	777 unique values 0 missing
Feature66	numeric	776 unique values 0 missing
Feature67	numeric	773 unique values 0 missing
Feature68	numeric	776 unique values 0 missing
Feature69	numeric	795 unique values 0 missing
Feature70	numeric	754 unique values 0 missing
Feature71	numeric	775 unique values 0 missing
Feature72	numeric	767 unique values 0 missing
Feature73	numeric	722 unique values 0 missing
Feature74	numeric	720 unique values 0 missing
Feature75	numeric	722 unique values 0 missing
Feature76	numeric	735 unique values 0 missing
Feature77	numeric	736 unique values 0 missing
Feature78	numeric	725 unique values 0 missing
Feature79	numeric	735 unique values 0 missing
Feature80	numeric	736 unique values 0 missing
Feature81	numeric	745 unique values 0 missing
Feature82	numeric	615 unique values 0 missing
Feature83	numeric	642 unique values 0 missing
Feature84	numeric	633 unique values 0 missing
Feature85	numeric	631 unique values 0 missing
Feature86	numeric	624 unique values 0 missing
Feature87	numeric	637 unique values 0 missing
Feature88	numeric	600 unique values 0 missing
Feature89	numeric	608 unique values 0 missing
Feature90	numeric	596 unique values 0 missing
Feature91	numeric	574 unique values 0 missing
Feature92	numeric	593 unique values 0 missing
Feature93	numeric	618 unique values 0 missing
Feature94	numeric	557 unique values 0 missing
Feature95	numeric	600 unique values 0 missing
Feature96	numeric	598 unique values 0 missing
Feature97	numeric	550 unique values 0 missing
Feature98	numeric	554 unique values 0 missing
Feature99	numeric	538 unique values 0 missing
Feature100	numeric	545 unique values 0 missing
Feature101	numeric	564 unique values 0 missing
Feature102	numeric	586 unique values 0 missing
Feature103	numeric	515 unique values 0 missing
Feature104	numeric	545 unique values 0 missing
Feature105	numeric	565 unique values 0 missing
Feature106	numeric	493 unique values 0 missing
Feature107	numeric	511 unique values 0 missing
Feature108	numeric	513 unique values 0 missing
Feature109	numeric	852 unique values 0 missing
Feature110	numeric	853 unique values 0 missing
Feature111	numeric	860 unique values 0 missing
Feature112	numeric	814 unique values 0 missing
Feature113	numeric	823 unique values 0 missing
Feature114	numeric	825 unique values 0 missing
Feature115	numeric	789 unique values 0 missing
Feature116	numeric	791 unique values 0 missing
Feature117	numeric	803 unique values 0 missing
Feature118	numeric	754 unique values 0 missing
Feature119	numeric	775 unique values 0 missing
Feature120	numeric	767 unique values 0 missing
Feature121	numeric	719 unique values 0 missing
Feature122	numeric	722 unique values 0 missing
Feature123	numeric	710 unique values 0 missing
Feature124	numeric	699 unique values 0 missing
Feature125	numeric	722 unique values 0 missing
Feature126	numeric	712 unique values 0 missing
Feature127	numeric	735 unique values 0 missing
Feature128	numeric	736 unique values 0 missing
Feature129	numeric	745 unique values 0 missing
Feature130	numeric	691 unique values 0 missing
Feature131	numeric	691 unique values 0 missing
Feature132	numeric	696 unique values 0 missing
Feature133	numeric	674 unique values 0 missing
Feature134	numeric	695 unique values 0 missing
Feature135	numeric	683 unique values 0 missing

Show first 100 features

62 properties

NumberOfInstances

2000

Number of instances (rows) of the dataset.

NumberOfFeatures

140

Number of attributes (columns) of the dataset.

NumberOfClasses

Number of distinct values of the target attribute (if it is nominal).

NumberOfMissingValues

Number of missing values in the dataset.

NumberOfInstancesWithMissingValues

Number of instances with at least one value missing.

NumberOfNumericFeatures

135

Number of numeric attributes.

NumberOfSymbolicFeatures

Number of nominal attributes.

ClassEntropy

Entropy of the target attribute values.

MeanNoiseToSignalRatio

An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.

Quartile2AttributeEntropy

Second quartile (Median) of entropy among attributes.

Dimensionality

0.07

Number of attributes divided by the number of instances.

MeanNominalAttDistinctValues

Average number of distinct values among the attributes of the nominal type.

Quartile2KurtosisOfNumericAtts

0.91

Second quartile (Median) of kurtosis among attributes of the numeric type.

EquivalentNumberOfAtts

Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.

MeanSkewnessOfNumericAtts

0.05

Mean skewness among attributes of the numeric type.

Quartile2MeansOfNumericAtts

-1.4

Second quartile (Median) of means among attributes of the numeric type.

MajorityClassPercentage

Percentage of instances belonging to the most frequent class.

MeanStdDevOfNumericAtts

46.09

Mean standard deviation of attributes of the numeric type.

Quartile2MutualInformation

Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

MajorityClassSize

Number of instances belonging to the most frequent class.

MinAttributeEntropy

Minimal entropy among attributes.

Quartile2SkewnessOfNumericAtts

0.03

Second quartile (Median) of skewness among attributes of the numeric type.

MaxAttributeEntropy

Maximum entropy among attributes.

MinKurtosisOfNumericAtts

-1.13

Minimum kurtosis among attributes of the numeric type.

PercentageOfBinaryFeatures

3.57

Percentage of binary attributes.

Quartile2StdDevOfNumericAtts

46.86

Second quartile (Median) of standard deviation of attributes of the numeric type.

MaxKurtosisOfNumericAtts

5.32

Maximum kurtosis among attributes of the numeric type.

MinMeansOfNumericAtts

-30.86

Minimum of means among attributes of the numeric type.

PercentageOfInstancesWithMissingValues

Percentage of instances having missing values.

Quartile3AttributeEntropy

Third quartile of entropy among attributes.

MaxMeansOfNumericAtts

130.2

Maximum of means among attributes of the numeric type.

MinMutualInformation

Minimal mutual information between the nominal attributes and the target attribute.

PercentageOfMissingValues

Percentage of missing values.

Quartile3KurtosisOfNumericAtts

2.02

Third quartile of kurtosis among attributes of the numeric type.

MaxMutualInformation

Maximum mutual information between the nominal attributes and the target attribute.

MinNominalAttDistinctValues

The minimal number of distinct values among attributes of the nominal type.

PercentageOfNumericFeatures

96.43

Percentage of numeric attributes.

Quartile3MeansOfNumericAtts

24.74

Third quartile of means among attributes of the numeric type.

MaxNominalAttDistinctValues

The maximum number of distinct values among attributes of the nominal type.

MinSkewnessOfNumericAtts

-0.54

Minimum skewness among attributes of the numeric type.

PercentageOfSymbolicFeatures

3.57

Percentage of nominal attributes.

Quartile3MutualInformation

Third quartile of mutual information between the nominal attributes and the target attribute.

MaxSkewnessOfNumericAtts

0.64

Maximum skewness among attributes of the numeric type.

MinStdDevOfNumericAtts

28.59

Minimum standard deviation of attributes of the numeric type.

Quartile1AttributeEntropy

First quartile of entropy among attributes.

Quartile3SkewnessOfNumericAtts

0.17

Third quartile of skewness among attributes of the numeric type.

MaxStdDevOfNumericAtts

64.24

Maximum standard deviation of attributes of the numeric type.

MinorityClassPercentage

Percentage of instances belonging to the least frequent class.

Quartile1KurtosisOfNumericAtts

0.08

First quartile of kurtosis among attributes of the numeric type.

Quartile3StdDevOfNumericAtts

54.29

Third quartile of standard deviation of attributes of the numeric type.

MeanAttributeEntropy

Average entropy of the attributes.

MinorityClassSize

Number of instances belonging to the least frequent class.

Quartile1MeansOfNumericAtts

-14.71

First quartile of means among attributes of the numeric type.

StdvNominalAttDistinctValues

Standard deviation of the number of distinct values among attributes of the nominal type.

MeanKurtosisOfNumericAtts

1.11

Mean kurtosis among attributes of the numeric type.

NumberOfBinaryFeatures

Number of binary attributes.

Quartile1MutualInformation

First quartile of mutual information between the nominal attributes and the target attribute.

MeanMeansOfNumericAtts

19.08

Mean of means among attributes of the numeric type.

Quartile1SkewnessOfNumericAtts

-0.09

First quartile of skewness among attributes of the numeric type.

AutoCorrelation

Average class difference between consecutive instances.

MeanMutualInformation

Average mutual information between the nominal attributes and the target attribute.

Quartile1StdDevOfNumericAtts

36.88

First quartile of standard deviation of attributes of the numeric type.

Show all 62 properties