Data
clean1

clean1

active ARFF public Visibility: public Uploaded 06-04-2017 by Pieter Gijsbers
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Derived from the Musk dataset: https://www.openml.org/d/1116

169 features

class (target)nominal2 unique values
0 missing
molecule_namenumeric92 unique values
0 missing
conformation_namenumeric476 unique values
0 missing
f1numeric70 unique values
0 missing
f2numeric147 unique values
0 missing
f3numeric138 unique values
0 missing
f4numeric147 unique values
0 missing
f5numeric38 unique values
0 missing
f6numeric205 unique values
0 missing
f7numeric124 unique values
0 missing
f8numeric191 unique values
0 missing
f9numeric143 unique values
0 missing
f10numeric215 unique values
0 missing
f11numeric180 unique values
0 missing
f12numeric187 unique values
0 missing
f13numeric154 unique values
0 missing
f14numeric165 unique values
0 missing
f15numeric139 unique values
0 missing
f16numeric119 unique values
0 missing
f17numeric177 unique values
0 missing
f18numeric168 unique values
0 missing
f19numeric196 unique values
0 missing
f20numeric155 unique values
0 missing
f21numeric213 unique values
0 missing
f22numeric115 unique values
0 missing
f23numeric213 unique values
0 missing
f24numeric170 unique values
0 missing
f25numeric110 unique values
0 missing
f26numeric186 unique values
0 missing
f27numeric175 unique values
0 missing
f28numeric142 unique values
0 missing
f29numeric157 unique values
0 missing
f30numeric138 unique values
0 missing
f31numeric66 unique values
0 missing
f32numeric159 unique values
0 missing
f33numeric138 unique values
0 missing
f34numeric204 unique values
0 missing
f35numeric126 unique values
0 missing
f36numeric113 unique values
0 missing
f37numeric91 unique values
0 missing
f38numeric164 unique values
0 missing
f39numeric116 unique values
0 missing
f40numeric177 unique values
0 missing
f41numeric146 unique values
0 missing
f42numeric162 unique values
0 missing
f43numeric163 unique values
0 missing
f44numeric151 unique values
0 missing
f45numeric163 unique values
0 missing
f46numeric195 unique values
0 missing
f47numeric138 unique values
0 missing
f48numeric208 unique values
0 missing
f49numeric194 unique values
0 missing
f50numeric160 unique values
0 missing
f51numeric178 unique values
0 missing
f52numeric113 unique values
0 missing
f53numeric147 unique values
0 missing
f54numeric202 unique values
0 missing
f55numeric173 unique values
0 missing
f56numeric165 unique values
0 missing
f57numeric149 unique values
0 missing
f58numeric141 unique values
0 missing
f59numeric164 unique values
0 missing
f60numeric198 unique values
0 missing
f61numeric141 unique values
0 missing
f62numeric136 unique values
0 missing
f63numeric92 unique values
0 missing
f64numeric185 unique values
0 missing
f65numeric129 unique values
0 missing
f66numeric80 unique values
0 missing
f67numeric33 unique values
0 missing
f68numeric153 unique values
0 missing
f69numeric142 unique values
0 missing
f70numeric165 unique values
0 missing
f71numeric135 unique values
0 missing
f72numeric119 unique values
0 missing
f73numeric176 unique values
0 missing
f74numeric202 unique values
0 missing
f75numeric165 unique values
0 missing
f76numeric45 unique values
0 missing
f77numeric128 unique values
0 missing
f78numeric189 unique values
0 missing
f79numeric162 unique values
0 missing
f80numeric144 unique values
0 missing
f81numeric213 unique values
0 missing
f82numeric126 unique values
0 missing
f83numeric152 unique values
0 missing
f84numeric201 unique values
0 missing
f85numeric178 unique values
0 missing
f86numeric132 unique values
0 missing
f87numeric165 unique values
0 missing
f88numeric193 unique values
0 missing
f89numeric155 unique values
0 missing
f90numeric165 unique values
0 missing
f91numeric125 unique values
0 missing
f92numeric107 unique values
0 missing
f93numeric102 unique values
0 missing
f94numeric168 unique values
0 missing
f95numeric115 unique values
0 missing
f96numeric161 unique values
0 missing
f97numeric189 unique values
0 missing
f98numeric141 unique values
0 missing
f99numeric91 unique values
0 missing
f100numeric167 unique values
0 missing
f101numeric166 unique values
0 missing
f102numeric125 unique values
0 missing
f103numeric166 unique values
0 missing
f104numeric161 unique values
0 missing
f105numeric142 unique values
0 missing
f106numeric210 unique values
0 missing
f107numeric155 unique values
0 missing
f108numeric217 unique values
0 missing
f109numeric151 unique values
0 missing
f110numeric156 unique values
0 missing
f111numeric145 unique values
0 missing
f112numeric205 unique values
0 missing
f113numeric176 unique values
0 missing
f114numeric163 unique values
0 missing
f115numeric201 unique values
0 missing
f116numeric183 unique values
0 missing
f117numeric133 unique values
0 missing
f118numeric185 unique values
0 missing
f119numeric142 unique values
0 missing
f120numeric164 unique values
0 missing
f121numeric124 unique values
0 missing
f122numeric168 unique values
0 missing
f123numeric187 unique values
0 missing
f124numeric155 unique values
0 missing
f125numeric159 unique values
0 missing
f126numeric109 unique values
0 missing
f127numeric213 unique values
0 missing
f128numeric177 unique values
0 missing
f129numeric188 unique values
0 missing
f130numeric131 unique values
0 missing
f131numeric148 unique values
0 missing
f132numeric161 unique values
0 missing
f133numeric176 unique values
0 missing
f134numeric190 unique values
0 missing
f135numeric186 unique values
0 missing
f136numeric158 unique values
0 missing
f137numeric166 unique values
0 missing
f138numeric171 unique values
0 missing
f139numeric205 unique values
0 missing
f140numeric184 unique values
0 missing
f141numeric179 unique values
0 missing
f142numeric170 unique values
0 missing
f143numeric154 unique values
0 missing
f144numeric134 unique values
0 missing
f145numeric29 unique values
0 missing
f146numeric60 unique values
0 missing
f147numeric53 unique values
0 missing
f148numeric176 unique values
0 missing
f149numeric167 unique values
0 missing
f150numeric174 unique values
0 missing
f151numeric117 unique values
0 missing
f152numeric105 unique values
0 missing
f153numeric97 unique values
0 missing
f154numeric135 unique values
0 missing
f155numeric175 unique values
0 missing
f156numeric133 unique values
0 missing
f157numeric65 unique values
0 missing
f158numeric217 unique values
0 missing
f159numeric165 unique values
0 missing
f160numeric126 unique values
0 missing
f161numeric194 unique values
0 missing
f162numeric127 unique values
0 missing
f163numeric112 unique values
0 missing
f164numeric61 unique values
0 missing
f165numeric109 unique values
0 missing
f166numeric146 unique values
0 missing

62 properties

476
Number of instances (rows) of the dataset.
169
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.
168
Number of numeric attributes.
1
Number of nominal attributes.
-14.18
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.
99.41
Percentage of numeric 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.
-1.83
Minimum skewness among attributes of the numeric type.
0.59
Percentage of nominal attributes.
0.5
Third quartile of skewness among attributes of the numeric type.
13.58
Maximum skewness among attributes of the numeric type.
11.96
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
93.72
Third quartile of standard deviation of attributes of the numeric type.
137.55
Maximum standard deviation of attributes of the numeric type.
43.49
Percentage of instances belonging to the least frequent class.
-1.04
First quartile of kurtosis 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.
207
Number of instances belonging to the least frequent class.
-86.43
First quartile of means among attributes of the numeric type.
3.6
Mean kurtosis among attributes of the numeric type.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
-50.57
Mean of means among attributes of the numeric type.
-0.47
First quartile of skewness among attributes of the numeric type.
1
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
66.3
First quartile of standard deviation of attributes of the numeric type.
0.99
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.
0.36
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
-0.43
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.
0.28
Mean skewness among attributes of the numeric type.
-56.21
Second quartile (Median) of means among attributes of the numeric type.
56.51
Percentage of instances belonging to the most frequent class.
78.76
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
269
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
-0.06
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.59
Minimum kurtosis among attributes of the numeric type.
0.59
Percentage of binary attributes.
79.49
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
215.74
Maximum kurtosis among attributes of the numeric type.
-265.09
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
1.47
Third quartile of kurtosis among attributes of the numeric type.
237.5
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.

12 tasks

31 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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