Data
musk

musk

active ARFF Publicly available Visibility: public Uploaded 07-10-2014 by Joaquin Vanschoren
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  • multi-instance mythbusting_1 study_1 study_15 study_20 study_34
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Author: Source: Unknown - Date unknown Please cite: Dataset from the MLRR repository: http://axon.cs.byu.edu:5000/ More infos: https://archive.ics.uci.edu/ml/datasets/Musk+(Version+2)

170 features

class (target)nominal2 unique values
0 missing
ID (row identifier)numeric6598 unique values
0 missing
molecule_namenominal102 unique values
0 missing
conformation_name (ignore)nominal6598 unique values
0 missing
f1numeric202 unique values
0 missing
f2numeric260 unique values
0 missing
f3numeric221 unique values
0 missing
f4numeric257 unique values
0 missing
f5numeric129 unique values
0 missing
f6numeric358 unique values
0 missing
f7numeric323 unique values
0 missing
f8numeric389 unique values
0 missing
f9numeric347 unique values
0 missing
f10numeric399 unique values
0 missing
f11numeric387 unique values
0 missing
f12numeric384 unique values
0 missing
f13numeric397 unique values
0 missing
f14numeric329 unique values
0 missing
f15numeric319 unique values
0 missing
f16numeric327 unique values
0 missing
f17numeric350 unique values
0 missing
f18numeric375 unique values
0 missing
f19numeric398 unique values
0 missing
f20numeric388 unique values
0 missing
f21numeric419 unique values
0 missing
f22numeric304 unique values
0 missing
f23numeric397 unique values
0 missing
f24numeric368 unique values
0 missing
f25numeric304 unique values
0 missing
f26numeric379 unique values
0 missing
f27numeric338 unique values
0 missing
f28numeric272 unique values
0 missing
f29numeric278 unique values
0 missing
f30numeric341 unique values
0 missing
f31numeric276 unique values
0 missing
f32numeric334 unique values
0 missing
f33numeric240 unique values
0 missing
f34numeric419 unique values
0 missing
f35numeric243 unique values
0 missing
f36numeric261 unique values
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f37numeric288 unique values
0 missing
f38numeric324 unique values
0 missing
f39numeric217 unique values
0 missing
f40numeric322 unique values
0 missing
f41numeric231 unique values
0 missing
f42numeric329 unique values
0 missing
f43numeric407 unique values
0 missing
f44numeric328 unique values
0 missing
f45numeric340 unique values
0 missing
f46numeric392 unique values
0 missing
f47numeric265 unique values
0 missing
f48numeric411 unique values
0 missing
f49numeric381 unique values
0 missing
f50numeric374 unique values
0 missing
f51numeric390 unique values
0 missing
f52numeric329 unique values
0 missing
f53numeric333 unique values
0 missing
f54numeric389 unique values
0 missing
f55numeric313 unique values
0 missing
f56numeric415 unique values
0 missing
f57numeric363 unique values
0 missing
f58numeric271 unique values
0 missing
f59numeric302 unique values
0 missing
f60numeric412 unique values
0 missing
f61numeric254 unique values
0 missing
f62numeric305 unique values
0 missing
f63numeric205 unique values
0 missing
f64numeric388 unique values
0 missing
f65numeric251 unique values
0 missing
f66numeric206 unique values
0 missing
f67numeric181 unique values
0 missing
f68numeric287 unique values
0 missing
f69numeric314 unique values
0 missing
f70numeric287 unique values
0 missing
f71numeric224 unique values
0 missing
f72numeric224 unique values
0 missing
f73numeric429 unique values
0 missing
f74numeric386 unique values
0 missing
f75numeric380 unique values
0 missing
f76numeric113 unique values
0 missing
f77numeric338 unique values
0 missing
f78numeric392 unique values
0 missing
f79numeric347 unique values
0 missing
f80numeric338 unique values
0 missing
f81numeric397 unique values
0 missing
f82numeric294 unique values
0 missing
f83numeric368 unique values
0 missing
f84numeric361 unique values
0 missing
f85numeric368 unique values
0 missing
f86numeric320 unique values
0 missing
f87numeric307 unique values
0 missing
f88numeric347 unique values
0 missing
f89numeric258 unique values
0 missing
f90numeric398 unique values
0 missing
f91numeric331 unique values
0 missing
f92numeric247 unique values
0 missing
f93numeric233 unique values
0 missing
f94numeric398 unique values
0 missing
f95numeric199 unique values
0 missing
f96numeric333 unique values
0 missing
f97numeric340 unique values
0 missing
f98numeric354 unique values
0 missing
f99numeric181 unique values
0 missing
f100numeric331 unique values
0 missing
f101numeric255 unique values
0 missing
f102numeric255 unique values
0 missing
f103numeric396 unique values
0 missing
f104numeric337 unique values
0 missing
f105numeric277 unique values
0 missing
f106numeric382 unique values
0 missing
f107numeric319 unique values
0 missing
f108numeric388 unique values
0 missing
f109numeric328 unique values
0 missing
f110numeric268 unique values
0 missing
f111numeric292 unique values
0 missing
f112numeric406 unique values
0 missing
f113numeric368 unique values
0 missing
f114numeric337 unique values
0 missing
f115numeric402 unique values
0 missing
f116numeric406 unique values
0 missing
f117numeric351 unique values
0 missing
f118numeric354 unique values
0 missing
f119numeric352 unique values
0 missing
f120numeric347 unique values
0 missing
f121numeric299 unique values
0 missing
f122numeric314 unique values
0 missing
f123numeric353 unique values
0 missing
f124numeric277 unique values
0 missing
f125numeric327 unique values
0 missing
f126numeric246 unique values
0 missing
f127numeric435 unique values
0 missing
f128numeric405 unique values
0 missing
f129numeric415 unique values
0 missing
f130numeric253 unique values
0 missing
f131numeric235 unique values
0 missing
f132numeric320 unique values
0 missing
f133numeric416 unique values
0 missing
f134numeric393 unique values
0 missing
f135numeric394 unique values
0 missing
f136numeric267 unique values
0 missing
f137numeric345 unique values
0 missing
f138numeric301 unique values
0 missing
f139numeric396 unique values
0 missing
f140numeric414 unique values
0 missing
f141numeric386 unique values
0 missing
f142numeric303 unique values
0 missing
f143numeric331 unique values
0 missing
f144numeric311 unique values
0 missing
f145numeric150 unique values
0 missing
f146numeric247 unique values
0 missing
f147numeric144 unique values
0 missing
f148numeric294 unique values
0 missing
f149numeric295 unique values
0 missing
f150numeric329 unique values
0 missing
f151numeric197 unique values
0 missing
f152numeric184 unique values
0 missing
f153numeric151 unique values
0 missing
f154numeric257 unique values
0 missing
f155numeric323 unique values
0 missing
f156numeric286 unique values
0 missing
f157numeric258 unique values
0 missing
f158numeric398 unique values
0 missing
f159numeric386 unique values
0 missing
f160numeric278 unique values
0 missing
f161numeric354 unique values
0 missing
f162numeric281 unique values
0 missing
f163numeric292 unique values
0 missing
f164numeric172 unique values
0 missing
f165numeric352 unique values
0 missing
f166numeric385 unique values
0 missing

62 properties

6598
Number of instances (rows) of the dataset.
170
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.
167
Number of numeric attributes.
3
Number of nominal attributes.
0.59
Percentage of binary attributes.
85.43
Second quartile (Median) of standard deviation of attributes of the numeric type.
4.58
Maximum entropy among attributes.
-1.62
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
4.58
Third quartile of entropy among attributes.
51.14
Maximum kurtosis among attributes of the numeric type.
-265.69
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
1.11
Third quartile of kurtosis among attributes of the numeric type.
201.76
Maximum of means among attributes of the numeric type.
0.62
Minimal mutual information between the nominal attributes and the target attribute.
98.24
Percentage of numeric attributes.
-3.12
Third quartile of means among attributes of the numeric type.
0.62
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
1.76
Percentage of nominal attributes.
0.62
Third quartile of mutual information between the nominal attributes and the target attribute.
102
The maximum number of distinct values among attributes of the nominal type.
-1.44
Minimum skewness among attributes of the numeric type.
4.58
First quartile of entropy among attributes.
0.66
Third quartile of skewness among attributes of the numeric type.
6.32
Maximum skewness among attributes of the numeric type.
13.98
Minimum standard deviation of attributes of the numeric type.
-1.04
First quartile of kurtosis among attributes of the numeric type.
101.74
Third quartile of standard deviation of attributes of the numeric type.
131.33
Maximum standard deviation of attributes of the numeric type.
15.41
Percentage of instances belonging to the least frequent class.
-87.33
First quartile of means among attributes of the numeric type.
70.71
Standard deviation of the number of distinct values among attributes of the nominal type.
4.58
Average entropy of the attributes.
1017
Number of instances belonging to the least frequent class.
0.62
First quartile of mutual information between the nominal attributes and the target attribute.
1.71
Mean kurtosis among attributes of the numeric type.
1
Number of binary attributes.
-0.2
First quartile of skewness among attributes of the numeric type.
-46.01
Mean of means among attributes of the numeric type.
69.42
First quartile of standard deviation of attributes of the numeric type.
1
Average class difference between consecutive instances.
0.62
Average mutual information between the nominal attributes and the target attribute.
4.58
Second quartile (Median) of entropy among attributes.
0.62
Entropy of the target attribute values.
6.39
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
-0.51
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.03
Number of attributes divided by the number of instances.
52
Average number of distinct values among the attributes of the nominal type.
-54.41
Second quartile (Median) of means among attributes of the numeric type.
1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
0.48
Mean skewness among attributes of the numeric type.
0.62
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
84.59
Percentage of instances belonging to the most frequent class.
85.95
Mean standard deviation of attributes of the numeric type.
0.1
Second quartile (Median) of skewness among attributes of the numeric type.
5581
Number of instances belonging to the most frequent class.
4.58
Minimal entropy among attributes.

20 tasks

66542 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
13306 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
45 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
1313 runs - target_feature: class
1308 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
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