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variousCancers_final

variousCancers_final

active ARFF Publicly available Visibility: public Uploaded 07-10-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: Data from the RSCTC 2010 Discovery Challenge. All datasets contain between 100 and 400 samples, characterized by values of 20,000 - 65,000 attributes. Samples are assigned to several (2-10) classes. All attributes are numeric and represent measurements from DNA microarrays. Attributes are normalized in some way - in test data you should expect similar distributions of attribute values as in the example data. Source: http://tunedit.org/challenge/RSCTC-2010-A

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0 missing
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0 missing
Var260numeric271 unique values
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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Var21764numeric356 unique values
0 missing
Var22020numeric307 unique values
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Var22276numeric318 unique values
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Var22532numeric352 unique values
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Var22788numeric313 unique values
0 missing
Var23044numeric336 unique values
0 missing
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0 missing
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0 missing
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0 missing
Var25092numeric308 unique values
0 missing
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0 missing
Var25604numeric295 unique values
0 missing
Var25860numeric316 unique values
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0 missing
Var26372numeric342 unique values
0 missing
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0 missing
Var26884numeric350 unique values
0 missing
Var27140numeric358 unique values
0 missing
Var27396numeric287 unique values
0 missing
Var27652numeric310 unique values
0 missing
Var27908numeric300 unique values
0 missing
Var28164numeric337 unique values
0 missing
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0 missing
Var28676numeric346 unique values
0 missing
Var28932numeric326 unique values
0 missing
Var29188numeric325 unique values
0 missing
Var29444numeric330 unique values
0 missing
Var29700numeric329 unique values
0 missing
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0 missing
Var30212numeric306 unique values
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Var30468numeric347 unique values
0 missing
Var30724numeric352 unique values
0 missing
Var30980numeric313 unique values
0 missing
Var31236numeric345 unique values
0 missing
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0 missing
Var31748numeric321 unique values
0 missing
Var32004numeric305 unique values
0 missing
Var32260numeric311 unique values
0 missing
Var32516numeric345 unique values
0 missing
Var32772numeric324 unique values
0 missing
Var33028numeric329 unique values
0 missing
Var33284numeric302 unique values
0 missing
Var33540numeric345 unique values
0 missing
Var33796numeric318 unique values
0 missing
Var34052numeric319 unique values
0 missing
Var34308numeric350 unique values
0 missing
Var34564numeric317 unique values
0 missing
Var34820numeric302 unique values
0 missing
Var35076numeric326 unique values
0 missing
Var35332numeric311 unique values
0 missing
Var35588numeric315 unique values
0 missing
Var35844numeric322 unique values
0 missing
Var36100numeric341 unique values
0 missing
Var36356numeric343 unique values
0 missing
Var36612numeric308 unique values
0 missing
Var36868numeric323 unique values
0 missing
Var37124numeric330 unique values
0 missing
Var37380numeric296 unique values
0 missing
Var37636numeric341 unique values
0 missing
Var37892numeric344 unique values
0 missing
Var38148numeric299 unique values
0 missing
Var38404numeric328 unique values
0 missing
Var38660numeric351 unique values
0 missing
Var38916numeric339 unique values
0 missing
Var39172numeric328 unique values
0 missing
Var39428numeric316 unique values
0 missing
Var39684numeric342 unique values
0 missing
Var39940numeric342 unique values
0 missing
Var40196numeric344 unique values
0 missing
Var40452numeric305 unique values
0 missing
Var40708numeric345 unique values
0 missing
Var40964numeric323 unique values
0 missing
Var41220numeric330 unique values
0 missing
Var41476numeric343 unique values
0 missing
Var41732numeric334 unique values
0 missing
Var41988numeric306 unique values
0 missing
Var42244numeric332 unique values
0 missing
Var42500numeric337 unique values
0 missing
Var42756numeric307 unique values
0 missing
Var43012numeric332 unique values
0 missing
Var43268numeric301 unique values
0 missing
Var43524numeric337 unique values
0 missing
Var43780numeric290 unique values
0 missing
Var44036numeric318 unique values
0 missing
Var44292numeric321 unique values
0 missing
Var44548numeric306 unique values
0 missing
Var44804numeric327 unique values
0 missing
Var45060numeric349 unique values
0 missing
Var45316numeric300 unique values
0 missing
Var45572numeric329 unique values
0 missing
Var45828numeric330 unique values
0 missing
Var46084numeric292 unique values
0 missing
Var46340numeric322 unique values
0 missing
Var46596numeric341 unique values
0 missing
Var46852numeric329 unique values
0 missing
Var47108numeric304 unique values
0 missing
Var47364numeric360 unique values
0 missing
Var47620numeric318 unique values
0 missing
Var47876numeric330 unique values
0 missing
Var48132numeric348 unique values
0 missing
Var48388numeric333 unique values
0 missing
Var48644numeric320 unique values
0 missing
Var48900numeric345 unique values
0 missing
Var49156numeric322 unique values
0 missing
Var49412numeric312 unique values
0 missing
Var49668numeric326 unique values
0 missing
Var49924numeric318 unique values
0 missing
Var50180numeric332 unique values
0 missing
Var50436numeric308 unique values
0 missing
Var50692numeric352 unique values
0 missing
Var50948numeric327 unique values
0 missing
Var51204numeric321 unique values
0 missing
Var51460numeric316 unique values
0 missing
Var51716numeric332 unique values
0 missing
Var51972numeric360 unique values
0 missing
Var52228numeric297 unique values
0 missing
Var52484numeric288 unique values
0 missing
Var52740numeric319 unique values
0 missing
Var52996numeric318 unique values
0 missing
Var53252numeric309 unique values
0 missing
Var53508numeric315 unique values
0 missing
Var53764numeric328 unique values
0 missing
Var54020numeric319 unique values
0 missing
Var54276numeric341 unique values
0 missing
Var54532numeric349 unique values
0 missing
Var5numeric276 unique values
0 missing
Var261numeric335 unique values
0 missing
Var517numeric338 unique values
0 missing
Var773numeric321 unique values
0 missing
Var1029numeric358 unique values
0 missing
Var1285numeric336 unique values
0 missing
Var1541numeric323 unique values
0 missing
Var1797numeric341 unique values
0 missing
Var2053numeric312 unique values
0 missing
Var2309numeric308 unique values
0 missing
Var2565numeric327 unique values
0 missing
Var2821numeric320 unique values
0 missing
Var3077numeric332 unique values
0 missing
Var3333numeric317 unique values
0 missing
Var3589numeric305 unique values
0 missing
Var3845numeric305 unique values
0 missing
Var4101numeric331 unique values
0 missing
Var4357numeric282 unique values
0 missing
Var4613numeric328 unique values
0 missing
Var4869numeric335 unique values
0 missing
Var5125numeric309 unique values
0 missing
Var5381numeric305 unique values
0 missing
Var5637numeric310 unique values
0 missing
Var5893numeric333 unique values
0 missing
Var6149numeric323 unique values
0 missing
Var6405numeric290 unique values
0 missing
Var6661numeric288 unique values
0 missing
Var6917numeric300 unique values
0 missing
Var7173numeric297 unique values
0 missing
Var7429numeric292 unique values
0 missing
Var7685numeric298 unique values
0 missing
Var7941numeric319 unique values
0 missing
Var8197numeric326 unique values
0 missing
Var8453numeric298 unique values
0 missing
Var8709numeric346 unique values
0 missing
Var8965numeric346 unique values
0 missing
Var9221numeric350 unique values
0 missing
Var9477numeric300 unique values
0 missing
Var9733numeric268 unique values
0 missing
Var9989numeric332 unique values
0 missing
Var10245numeric320 unique values
0 missing
Var10501numeric348 unique values
0 missing
Var10757numeric322 unique values
0 missing
Var11013numeric317 unique values
0 missing
Var11269numeric337 unique values
0 missing
Var11525numeric341 unique values
0 missing
Var11781numeric330 unique values
0 missing
Var12037numeric349 unique values
0 missing
Var12293numeric316 unique values
0 missing
Var12549numeric320 unique values
0 missing
Var12805numeric309 unique values
0 missing
Var13061numeric310 unique values
0 missing
Var13317numeric326 unique values
0 missing
Var13573numeric322 unique values
0 missing
Var13829numeric335 unique values
0 missing
Var14085numeric327 unique values
0 missing
Var14341numeric349 unique values
0 missing
Var14597numeric332 unique values
0 missing
Var14853numeric338 unique values
0 missing
Var15109numeric325 unique values
0 missing
Var15365numeric335 unique values
0 missing
Var15621numeric306 unique values
0 missing
Var15877numeric334 unique values
0 missing
Var16133numeric323 unique values
0 missing
Var16389numeric323 unique values
0 missing
Var16645numeric323 unique values
0 missing
Var16901numeric324 unique values
0 missing
Var17157numeric338 unique values
0 missing
Var17413numeric334 unique values
0 missing
Var17669numeric312 unique values
0 missing
Var17925numeric339 unique values
0 missing
Var18181numeric318 unique values
0 missing
Var18437numeric295 unique values
0 missing
Var18693numeric319 unique values
0 missing
Var18949numeric334 unique values
0 missing
Var19205numeric347 unique values
0 missing
Var19461numeric308 unique values
0 missing
Var19717numeric304 unique values
0 missing
Var19973numeric343 unique values
0 missing
Var20229numeric336 unique values
0 missing
Var20485numeric336 unique values
0 missing
Var20741numeric328 unique values
0 missing
Var20997numeric349 unique values
0 missing
Var21253numeric336 unique values
0 missing
Var21509numeric329 unique values
0 missing
Var21765numeric332 unique values
0 missing
Var22021numeric336 unique values
0 missing
Var22277numeric353 unique values
0 missing
Var22533numeric323 unique values
0 missing
Var22789numeric331 unique values
0 missing
Var23045numeric272 unique values
0 missing
Var23301numeric344 unique values
0 missing
Var23557numeric312 unique values
0 missing
Var23813numeric348 unique values
0 missing
Var24069numeric289 unique values
0 missing
Var24325numeric296 unique values
0 missing
Var24581numeric296 unique values
0 missing
Var24837numeric338 unique values
0 missing
Var25093numeric313 unique values
0 missing
Var25349numeric301 unique values
0 missing
Var25605numeric301 unique values
0 missing
Var25861numeric337 unique values
0 missing
Var26117numeric316 unique values
0 missing
Var26373numeric332 unique values
0 missing
Var26629numeric322 unique values
0 missing
Var26885numeric330 unique values
0 missing
Var27141numeric331 unique values
0 missing
Var27397numeric323 unique values
0 missing
Var27653numeric343 unique values
0 missing
Var27909numeric338 unique values
0 missing
Var28165numeric332 unique values
0 missing
Var28421numeric305 unique values
0 missing
Var28677numeric309 unique values
0 missing
Var28933numeric313 unique values
0 missing
Var29189numeric317 unique values
0 missing
Var29445numeric277 unique values
0 missing
Var29701numeric322 unique values
0 missing
Var29957numeric323 unique values
0 missing
Var30213numeric352 unique values
0 missing
Var30469numeric330 unique values
0 missing
Var30725numeric324 unique values
0 missing
Var30981numeric348 unique values
0 missing
Var31237numeric329 unique values
0 missing
Var31493numeric330 unique values
0 missing
Var31749numeric338 unique values
0 missing
Var32005numeric338 unique values
0 missing
Var32261numeric327 unique values
0 missing
Var32517numeric322 unique values
0 missing
Var32773numeric330 unique values
0 missing
Var33029numeric351 unique values
0 missing
Var33285numeric347 unique values
0 missing
Var33541numeric310 unique values
0 missing
Var33797numeric296 unique values
0 missing
Var34053numeric300 unique values
0 missing
Var34309numeric340 unique values
0 missing
Var34565numeric359 unique values
0 missing
Var34821numeric329 unique values
0 missing
Var35077numeric307 unique values
0 missing
Var35333numeric359 unique values
0 missing
Var35589numeric343 unique values
0 missing
Var35845numeric346 unique values
0 missing
Var36101numeric300 unique values
0 missing
Var36357numeric300 unique values
0 missing

107 properties

383
Number of instances (rows) of the dataset.
54676
Number of attributes (columns) of the dataset.
9
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.
54675
Number of numeric attributes.
1
Number of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.37
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.51
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.59
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
16
Number of instances belonging to the least frequent class.
0
Percentage of nominal attributes.
0.45
Third quartile of skewness among attributes of the numeric type.
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.35
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1.8
Mean kurtosis among attributes of the numeric type.
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
0.47
Third quartile of standard deviation of attributes of the numeric type.
0.79
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.33
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
2.22
Mean of means among attributes of the numeric type.
0.27
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.02
First quartile of kurtosis among attributes of the numeric type.
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.37
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.51
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.59
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.55
First quartile of means among attributes of the numeric type.
0.35
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.35
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.79
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.33
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
9
Average number of distinct values among the attributes of the nominal type.
-0.58
First quartile of skewness among attributes of the numeric type.
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.37
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.59
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
-0.02
Mean skewness among attributes of the numeric type.
0.28
First quartile of standard deviation of attributes of the numeric type.
0.35
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.13
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
40.47
Percentage of instances belonging to the most frequent class.
0.41
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.88
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
2.69
Entropy of the target attribute values.
0.83
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
155
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
2.13
Second quartile (Median) of means among attributes of the numeric type.
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.82
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.35
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.5
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
112.61
Maximum kurtosis among attributes of the numeric type.
0.26
Minimum of means among attributes of the numeric type.
-0.12
Second quartile (Median) of skewness among attributes of the numeric type.
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
5.3
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0.37
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
142.76
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
9
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
Third quartile of entropy among attributes.
0.51
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
9
The maximum number of distinct values among attributes of the nominal type.
-7.14
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
2.31
Third quartile of kurtosis among attributes of the numeric type.
0.2
Average class difference between consecutive instances.
0.35
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
8.32
Maximum skewness among attributes of the numeric type.
0.12
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
2.81
Third quartile of means among attributes of the numeric type.
0.79
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.33
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2.03
Maximum standard deviation of attributes of the numeric type.
4.18
Percentage of instances belonging to the least frequent class.
100
Percentage of numeric attributes.

14 tasks

1 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Decision
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Decision
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: Decision
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
0 runs - estimation_procedure: 50 times Clustering
Define a new task