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PopularKids

PopularKids

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Author: Source: Unknown - Date unknown Please cite: Datasets of Data And Story Library, project illustrating use of basic statistic methods, converted to arff format by Hakan Kjellerstrand. Source: TunedIT: http://tunedit.org/repo/DASL DASL file http://lib.stat.cmu.edu/DASL/Datafiles/PopularKids.html Students' Goals , What Makes Kids Popular Reference: Chase, M. A., and Dummer, G. M. (1992), "The Role of Sports as a Social Determinant for Children," Research Quarterly for Exercise and Sport, 63, 418-424 Authorization: Contact authors Description: Subjects were students in grades 4-6 from three school districts in Ingham and Clinton Counties, Michigan. Chase and Dummer stratified their sample, selecting students from urban, suburban, and rural school districts with approximately 1/3 of their sample coming from each district. Students indicated whether good grades, athletic ability, or popularity was most important to them. They also ranked four factors: grades, sports, looks, and money, in order of their importance for popularity. The questionnaire also asked for gender, grade level, and other demographic information. Number of cases: 478 Variable Names: Gender: Boy or girl Grade: 4, 5 or 6 Age: Age in years Race: White, Other Urban/Rural: Rural, Suburban, or Urban school district School: Brentwood Elementary, Brentwood Middle, Ridge, Sand, Eureka, Brown, Main, Portage, Westdale Middle Goals: Student's choice in the personal goals question where options were 1 = Make Good Grades, 2 = Be Popular, 3 = Be Good in Sports Grades: Rank of "make good grades" (1=most important for popularity, 4=least important) Sports: Rank of "being good at sports" (1=most important for popularity, 4=least important) Looks: Rank of "being handsome or pretty" (1=most important for popularity, 4=least important) Money: Rank of "having lots of money" (1=most important for popularity, 4=least important)

11 features

Goals (target)nominal3 unique values
0 missing
Gendernominal2 unique values
0 missing
Gradenumeric3 unique values
0 missing
Agenumeric6 unique values
0 missing
Racenominal2 unique values
0 missing
Urban/Ruralnominal3 unique values
0 missing
Schoolnominal9 unique values
0 missing
Gradesnumeric4 unique values
0 missing
Sportsnumeric4 unique values
0 missing
Looksnumeric4 unique values
0 missing
Moneynumeric4 unique values
0 missing
Show all 11 features

107 properties

NumberOfInstances
478
Number of instances (rows) of the dataset.
NumberOfFeatures
11
Number of attributes (columns) of the dataset.
NumberOfClasses
3
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
6
Number of numeric attributes.
NumberOfSymbolicFeatures
5
Number of nominal attributes.
AutoCorrelation
0.43
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.56
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
0.46
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
0.16
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
0.56
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
0.46
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
0.16
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
0.56
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
0.46
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
0.16
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
1.47
Entropy of the target attribute values.
DecisionStumpAUC
0.56
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.52
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.07
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.02
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
50.14
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.5
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.5
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.5
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
51.67
Percentage of instances belonging to the most frequent class.
MajorityClassSize
247
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
3.07
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
-0.28
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
10.42
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.05
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
9
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
0.48
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
1.08
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
1.51
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
-0.9
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
4.26
Mean of means among attributes of the numeric type.
MeanMutualInformation
0.03
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
50.65
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
3.8
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
-0.07
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
0.97
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
0.39
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.34
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
2.09
Minimum of means among attributes of the numeric type.
MinMutualInformation
0
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.9
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.78
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
18.83
Percentage of instances belonging to the least frequent class.
MinorityClassSize
90
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.5
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
2
Number of binary attributes.
PercentageOfBinaryFeatures
18.18
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
54.55
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
45.45
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.54
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-1.28
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
2.1
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
0.01
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
-0.41
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.91
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
1.29
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
-0.98
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
2.91
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.03
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
-0.1
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
0.98
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
2.7
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
-0.48
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
6.46
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.05
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
0.46
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
1.07
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.47
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.15
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.47
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.15
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.47
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.15
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.56
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.56
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.56
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
2.95
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.51
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.15
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

14 tasks

Supervised Classification on PopularKids
405 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Goals
Supervised Classification on PopularKids
188 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Goals
Supervised Data Stream Classification on PopularKids
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: Goals
Clustering on PopularKids
0 runs
Clustering on PopularKids
0 runs - estimation_procedure: 50 times Clustering
Clustering on PopularKids
0 runs - estimation_procedure: 50 times Clustering
Clustering on PopularKids
0 runs - estimation_procedure: 50 times Clustering
Clustering on PopularKids
0 runs - estimation_procedure: 50 times Clustering
Clustering on PopularKids
0 runs - estimation_procedure: 50 times Clustering
Clustering on PopularKids
0 runs - estimation_procedure: 50 times Clustering
Clustering on PopularKids
0 runs - estimation_procedure: 50 times Clustering
Clustering on PopularKids
0 runs - estimation_procedure: 50 times Clustering
Clustering on PopularKids
0 runs - estimation_procedure: 50 times Clustering
Clustering on PopularKids
0 runs - estimation_procedure: 50 times Clustering
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