Data
ozone_level

ozone_level

active ARFF Publicly available Visibility: public Uploaded 20-08-2014 by Tobias Kuehn
0 likes downloaded by 1 people , 1 total downloads 2 issues 2 downvotes
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Missing default_target_attribute1User 970
Seems to be a classification problem1User 5824


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Author: Source: Unknown - Please cite: 1. Title: Ozone Level Detection 2. Source: Kun Zhang zhang.kun05 '@' gmail.com Department of Computer Science, Xavier University of Lousiana Wei Fan wei.fan '@' gmail.com IBM T.J.Watson Research XiaoJing Yuan xyuan '@' uh.edu Engineering Technology Department, College of Technology, University of Houston 3. Past Usage: Forecasting skewed biased stochastic ozone days: analyses, solutions and beyond, Knowledge and Information Systems, Vol. 14, No. 3, 2008. Discusses details about the dataset, its use as well as various experiments (both cross-validation and streaming) using many state-of-the-art methods. A shorter version of the paper (does not contain some detailed experiments as the journal paper above) is in: Forecasting Skewed Biased Stochastic Ozone Days: Analyses and Solutions. ICDM 2006: 753-764 4. Relevant Information: The following are specifications for several most important attributes that are highly valued by Texas Commission on Environmental Quality (TCEQ). More details can be found in the two relevant papers. -- O 3 - Local ozone peak prediction -- Upwind - Upwind ozone background level -- EmFactor - Precursor emissions related factor -- Tmax - Maximum temperature in degrees F -- Tb - Base temperature where net ozone production begins (50 F) -- SRd - Solar radiation total for the day -- WSa - Wind speed near sunrise (using 09-12 UTC forecast mode) -- WSp - Wind speed mid-day (using 15-21 UTC forecast mode) 5. Number of Instances: 2536 6. Number of Attributes: 73 7. Attribute Information: 1,0 | two classes 1: ozone day, 0: normal day

73 features

Class (target)numeric2 unique values
0 missing
WSR0nominal69 unique values
0 missing
WSR1nominal71 unique values
0 missing
WSR2nominal66 unique values
0 missing
WSR3nominal67 unique values
0 missing
WSR4nominal65 unique values
0 missing
WSR5nominal64 unique values
0 missing
WSR6nominal67 unique values
0 missing
WSR7nominal68 unique values
0 missing
WSR8nominal70 unique values
0 missing
WSR9nominal71 unique values
0 missing
WSR10nominal77 unique values
0 missing
WSR11nominal78 unique values
0 missing
WSR12nominal78 unique values
0 missing
WSR13nominal79 unique values
0 missing
WSR14nominal78 unique values
0 missing
WSR15nominal79 unique values
0 missing
WSR16nominal73 unique values
0 missing
WSR17nominal74 unique values
0 missing
WSR18nominal71 unique values
0 missing
WSR19nominal66 unique values
0 missing
WSR20nominal69 unique values
0 missing
WSR21nominal70 unique values
0 missing
WSR22nominal69 unique values
0 missing
WSR23nominal66 unique values
0 missing
WSR_PKnominal75 unique values
0 missing
WSR_AVnominal56 unique values
0 missing
T0nominal283 unique values
0 missing
T1nominal285 unique values
0 missing
T2nominal288 unique values
0 missing
T3nominal284 unique values
0 missing
T4nominal284 unique values
0 missing
T5nominal293 unique values
0 missing
T6nominal296 unique values
0 missing
T7nominal312 unique values
0 missing
T8nominal314 unique values
0 missing
T9nominal315 unique values
0 missing
T10nominal328 unique values
0 missing
T11nominal331 unique values
0 missing
T12nominal335 unique values
0 missing
T13nominal336 unique values
0 missing
T14nominal336 unique values
0 missing
T15nominal340 unique values
0 missing
T16nominal338 unique values
0 missing
T17nominal330 unique values
0 missing
T18nominal322 unique values
0 missing
T19nominal307 unique values
0 missing
T20nominal303 unique values
0 missing
T21nominal295 unique values
0 missing
T22nominal288 unique values
0 missing
T23nominal285 unique values
0 missing
T_PKnominal331 unique values
0 missing
T_AVnominal297 unique values
0 missing
T85nominal252 unique values
0 missing
RH85nominal101 unique values
0 missing
U85nominal1290 unique values
0 missing
V85nominal1463 unique values
0 missing
HT85nominal369 unique values
0 missing
T70nominal246 unique values
0 missing
RH70nominal101 unique values
0 missing
U70nominal1538 unique values
0 missing
V70nominal1430 unique values
0 missing
HT70nominal442 unique values
0 missing
T50nominal187 unique values
0 missing
RH50nominal101 unique values
0 missing
U50nominal1688 unique values
0 missing
V50nominal1511 unique values
0 missing
HT50nominal86 unique values
0 missing
KInominal1049 unique values
0 missing
TTnominal658 unique values
0 missing
SLPnominal72 unique values
0 missing
SLP_nominal57 unique values
0 missing
Precpnominal175 unique values
0 missing

107 properties

2536
Number of instances (rows) of the dataset.
73
Number of attributes (columns) of the dataset.
0
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.
1
Number of numeric attributes.
72
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.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
315.39
Average number of distinct values among the attributes of the nominal type.
5.64
First quartile of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
392.24
Standard deviation of the number of distinct values among attributes of the nominal type.
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
5.64
Mean skewness among attributes of the numeric type.
0.17
First quartile of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.17
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
29.83
Second quartile (Median) of kurtosis among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Entropy of the target attribute values.
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Number of instances belonging to the most frequent class.
29.83
Minimum kurtosis among attributes of the numeric type.
0.03
Second quartile (Median) of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
0.03
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
29.83
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
5.64
Second quartile (Median) of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0.03
Maximum of means among attributes of the numeric type.
56
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
0.17
Second quartile (Median) of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.03
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
5.64
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
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.
1688
The maximum number of distinct values among attributes of the nominal type.
0.17
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
29.83
Third quartile of kurtosis among attributes of the numeric type.
0.95
Average class difference between consecutive instances.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
5.64
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
1.37
Percentage of numeric attributes.
0.03
Third quartile of means among attributes of the numeric type.
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.17
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
98.63
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
5.64
Third quartile of skewness among attributes of the numeric type.
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
29.83
Mean kurtosis among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
29.83
First quartile of kurtosis among attributes of the numeric type.
0.17
Third quartile of standard deviation of attributes of the numeric type.
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.03
Mean of means among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.03
First quartile of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

4 tasks

0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: Class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: Class
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