Data
synthetic_control

synthetic_control

active ARFF Publicly available Visibility: public Uploaded 27-09-2014 by Joaquin Vanschoren
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  • artificial OpenML100 study_1 study_123 study_135 study_14 study_34 study_52 study_7 time_series
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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/

62 features

class (target)nominal6 unique values
0 missing
index (row identifier)nominal600 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
col_16numeric599 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
col_31numeric600 unique values
0 missing
col_32numeric600 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

107 properties

600
Number of instances (rows) of the dataset.
62
Number of attributes (columns) of the dataset.
6
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.
60
Number of numeric attributes.
2
Number of nominal attributes.
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.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
6
Average number of distinct values among the attributes of the nominal type.
-0.05
First quartile of skewness among attributes of the numeric type.
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.03
Mean skewness among attributes of the numeric type.
5.85
First quartile of standard deviation of attributes of the numeric type.
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
9.75
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
0.04
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
16.67
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
-0.75
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
2.58
Entropy of the target attribute values.
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
100
Number of instances belonging to the most frequent class.
-1.21
Minimum kurtosis among attributes of the numeric type.
30.09
Second quartile (Median) of means among attributes of the numeric type.
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
28.15
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.67
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
0.6
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Second quartile (Median) of skewness among attributes of the numeric type.
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
32.23
Maximum of means among attributes of the numeric type.
6
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
9.57
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.1
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
-0.69
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.13
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.
6
The maximum number of distinct values among attributes of the nominal type.
3.5
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
0.03
Third quartile of kurtosis among attributes of the numeric type.
0.99
Average class difference between consecutive instances.
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.93
Maximum skewness among attributes of the numeric type.
16.67
Percentage of instances belonging to the least frequent class.
96.77
Percentage of numeric attributes.
30.46
Third quartile of means among attributes of the numeric type.
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
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.13
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
15.6
Maximum standard deviation of attributes of the numeric type.
100
Number of instances belonging to the least frequent class.
3.23
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
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
0.13
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
0.08
Third quartile of skewness among attributes of the numeric type.
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
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
-0.56
Mean kurtosis among attributes of the numeric type.
0.05
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-1.12
First quartile of kurtosis among attributes of the numeric type.
13.53
Third quartile of standard deviation of attributes of the numeric type.
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
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.13
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
30.09
Mean of means among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
29.73
First quartile of means among attributes of the numeric type.
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.13
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

37 tasks

9283 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
31 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
44 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
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0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
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