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synthetic_control

synthetic_control

active ARFF Publicly available Visibility: public Uploaded 27-09-2014 by Felicia West
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  • artificial OpenML100 study_1 study_123 study_135 study_14 study_34 study_52 study_7 time_series study_236 study_293
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Author: Dr Robert Alcock (rob@skyblue.csd.auth.gr) Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Synthetic+Control+Chart+Time+Series) - 1999 Please cite: ### Description Synthetic Control Chart Time Series. This is actually time series classification. ### Sources ``` * Original Owner and Donor Dr Robert Alcock rob@skyblue.csd.auth.gr ``` ### Dataset Information This data consists of synthetically generated control charts. This dataset contains 600 examples of control charts synthetically generated by the process in Alcock and Manolopoulos (1999). There are six different classes of control charts: ``` 1. Normal 2. Cyclic 3. Increasing trend 4. Decreasing trend 5. Upward shift 6. Downward shift ```` ### Relevante papers Alcock R.J. and Manolopoulos Y. Time-Series Similarity Queries Employing a Feature-Based Approach. 7th Hellenic Conference on Informatics. August 27-29. Ioannina,Greece 1999. D.T. Pham and A.B. Chan "Control Chart Pattern Recognition using a New Type of Self Organizing Neural Network" Proc. Instn, Mech, Engrs. Vol 212, No 1, pp 115-127 1998. ### References 1. http://skyblue.csd.auth.gr/~rob/ 2. mailto:rob@skyblue.csd.auth.gr 3. http://kdd.ics.uci.edu/ 4. http://www.ics.uci.edu/ 5. http://www.uci.edu/

61 features

class (target)nominal6 unique values
0 missing
col_32numeric600 unique values
0 missing
col_31numeric600 unique values
0 missing
col_33numeric599 unique values
0 missing
col_34numeric600 unique values
0 missing
col_35numeric600 unique values
0 missing
col_36numeric599 unique values
0 missing
col_37numeric600 unique values
0 missing
col_38numeric599 unique values
0 missing
col_39numeric600 unique values
0 missing
col_40numeric596 unique values
0 missing
col_41numeric600 unique values
0 missing
col_42numeric600 unique values
0 missing
col_43numeric600 unique values
0 missing
col_44numeric599 unique values
0 missing
col_45numeric600 unique values
0 missing
col_46numeric600 unique values
0 missing
col_47numeric598 unique values
0 missing
col_48numeric600 unique values
0 missing
col_49numeric600 unique values
0 missing
col_50numeric600 unique values
0 missing
col_51numeric599 unique values
0 missing
col_52numeric600 unique values
0 missing
col_53numeric600 unique values
0 missing
col_54numeric600 unique values
0 missing
col_55numeric599 unique values
0 missing
col_56numeric599 unique values
0 missing
col_57numeric600 unique values
0 missing
col_58numeric600 unique values
0 missing
col_59numeric599 unique values
0 missing
col_60numeric599 unique values
0 missing
col_16numeric599 unique values
0 missing
col_1numeric597 unique values
0 missing
col_2numeric600 unique values
0 missing
col_3numeric599 unique values
0 missing
col_4numeric598 unique values
0 missing
col_5numeric597 unique values
0 missing
col_6numeric596 unique values
0 missing
col_7numeric596 unique values
0 missing
col_8numeric598 unique values
0 missing
col_9numeric599 unique values
0 missing
col_10numeric596 unique values
0 missing
col_11numeric599 unique values
0 missing
col_12numeric600 unique values
0 missing
col_13numeric600 unique values
0 missing
col_14numeric597 unique values
0 missing
col_15numeric596 unique values
0 missing
index (row identifier)nominal600 unique values
0 missing
col_17numeric599 unique values
0 missing
col_18numeric600 unique values
0 missing
col_19numeric597 unique values
0 missing
col_20numeric598 unique values
0 missing
col_21numeric595 unique values
0 missing
col_22numeric596 unique values
0 missing
col_23numeric597 unique values
0 missing
col_24numeric599 unique values
0 missing
col_25numeric598 unique values
0 missing
col_26numeric600 unique values
0 missing
col_27numeric597 unique values
0 missing
col_28numeric599 unique values
0 missing
col_29numeric599 unique values
0 missing
col_30numeric597 unique values
0 missing
Show all 61 features

107 properties

NumberOfInstances
600
Number of instances (rows) of the dataset.
NumberOfFeatures
61
Number of attributes (columns) of the dataset.
NumberOfClasses
6
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
60
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
AutoCorrelation
0.99
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.94
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
CfsSubsetEval_DecisionStumpErrRate
0.12
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
CfsSubsetEval_DecisionStumpKappa
0.85
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
CfsSubsetEval_NaiveBayesAUC
0.94
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
CfsSubsetEval_NaiveBayesErrRate
0.12
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
CfsSubsetEval_NaiveBayesKappa
0.85
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
CfsSubsetEval_kNN1NAUC
0.94
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
CfsSubsetEval_kNN1NErrRate
0.12
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
CfsSubsetEval_kNN1NKappa
0.85
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
ClassEntropy
2.58
Entropy of the target attribute values.
DecisionStumpAUC
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.67
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.1
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
16.67
Percentage of instances belonging to the most frequent class.
MajorityClassSize
100
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
0.6
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
32.23
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
6
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
0.93
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
15.6
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
-0.56
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
30.09
Mean of means among attributes of the numeric type.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
6
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
0.03
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
9.75
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.21
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
28.15
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
6
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.69
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
3.5
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
16.67
Percentage of instances belonging to the least frequent class.
MinorityClassSize
100
Number of instances belonging to the least frequent class.
NaiveBayesAUC
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.05
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
0
Number of binary attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
98.36
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
1.64
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-1.12
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
29.73
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
-0.05
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
5.85
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
-0.75
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
30.09
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
0
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
9.57
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
0.03
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
30.46
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
0.08
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
13.53
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.04
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

51 tasks

Supervised Classification on synthetic_control
12631 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
Supervised Classification on synthetic_control
31 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Supervised Classification on synthetic_control
1 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: class
Supervised Classification on synthetic_control
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on synthetic_control
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on synthetic_control
44 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on synthetic_control
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on synthetic_control
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on synthetic_control
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on synthetic_control
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on synthetic_control
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on synthetic_control
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on synthetic_control
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on synthetic_control
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on synthetic_control
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on synthetic_control
0 runs - target_feature: class
Clustering on synthetic_control
0 runs
Clustering on synthetic_control
0 runs - estimation_procedure: 50 times Clustering
Clustering on synthetic_control
0 runs - estimation_procedure: 50 times Clustering
Clustering on synthetic_control
0 runs - estimation_procedure: 50 times Clustering
Clustering on synthetic_control
0 runs - estimation_procedure: 50 times Clustering
Clustering on synthetic_control
0 runs - estimation_procedure: 50 times Clustering
Clustering on synthetic_control
0 runs - estimation_procedure: 50 times Clustering
Clustering on synthetic_control
0 runs - estimation_procedure: 50 times Clustering
Clustering on synthetic_control
0 runs - estimation_procedure: 50 times Clustering
Clustering on synthetic_control
0 runs - estimation_procedure: 50 times Clustering
Clustering on synthetic_control
0 runs - estimation_procedure: 50 times Clustering
Subgroup Discovery on synthetic_control
1304 runs - target_feature: class
Subgroup Discovery on synthetic_control
1301 runs - target_feature: class
Subgroup Discovery on synthetic_control
1301 runs - target_feature: class
Subgroup Discovery on synthetic_control
1300 runs - target_feature: class
Subgroup Discovery on synthetic_control
1299 runs - target_feature: class
Subgroup Discovery on synthetic_control
1297 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
Subgroup Discovery on synthetic_control
0 runs - target_feature: class
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