DEVELOPMENT... OpenML
Data
kdd_internet_usage

kdd_internet_usage

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Felicia West
0 likes downloaded by 6 people , 6 total downloads 0 issues 0 downvotes
  • binarized binarized_regression_problem mythbusting_1 study_1 study_144 study_15 study_20 study_41 study_293
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Author: Source: Unknown - Date unknown Please cite: Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and all others as negative ('N'). Originally converted by Quan Sun.

69 features

Who_Pays_for_Access_Work (target)nominal2 unique values
0 missing
Not_Purchasing_Not_optionnominal2 unique values
0 missing
Opinions_on_Censorshipnominal4 unique values
0 missing
Not_Purchasing_Not_applicablenominal2 unique values
0 missing
Not_Purchasing_No_creditnominal2 unique values
0 missing
Not_Purchasing_Never_triednominal2 unique values
0 missing
Not_Purchasing_Judge_qualitynominal2 unique values
0 missing
Not_Purchasing_Enough_infonominal2 unique values
0 missing
Not_Purchasing_Easier_locallynominal2 unique values
0 missing
Not_Purchasing_Company_policynominal2 unique values
0 missing
Not_Purchasing_Cant_findnominal2 unique values
0 missing
Not_Purchasing_Bad_pressnominal2 unique values
0 missing
Not_Purchasing_Bad_experiencenominal2 unique values
0 missing
Racenominal8 unique values
0 missing
Primary_Place_of_WWW_Accessnominal9 unique values
0 missing
Primary_Languagenominal119 unique values
0 missing
Primary_Computing_Platformnominal11 unique values
2699 missing
Most_Import_Issue_Facing_the_Internetnominal9 unique values
0 missing
Registered_to_Votenominal4 unique values
0 missing
Who_Pays_for_Access_Selfnominal2 unique values
0 missing
Who_Pays_for_Access_Schoolnominal2 unique values
0 missing
Who_Pays_for_Access_Parentsnominal2 unique values
0 missing
Who_Pays_for_Access_Othernominal2 unique values
0 missing
Who_Pays_for_Access_Dont_Knownominal2 unique values
0 missing
Web_Page_Creationnominal3 unique values
0 missing
Web_Orderingnominal3 unique values
0 missing
Sexual_Preferencenominal6 unique values
0 missing
Not_Purchasing_Othernominal2 unique values
0 missing
Not_Purchasing_Unfamiliar_vendornominal2 unique values
0 missing
Not_Purchasing_Uncomfortablenominal2 unique values
0 missing
Not_Purchasing_Too_complicatednominal2 unique values
0 missing
Not_Purchasing_Securitynominal2 unique values
0 missing
Not_Purchasing_Receiptnominal2 unique values
0 missing
Not_Purchasing_Privacynominal2 unique values
0 missing
Not_Purchasing_Prefer_peoplenominal2 unique values
0 missing
Community_Membership_Professionalnominal2 unique values
0 missing
Disability_Not_Saynominal2 unique values
0 missing
Disability_Not_Impairednominal2 unique values
0 missing
Disability_Motornominal2 unique values
0 missing
Disability_Hearingnominal2 unique values
0 missing
Disability_Cognitivenominal2 unique values
0 missing
Countrynominal129 unique values
0 missing
Community_Membership_Supportnominal2 unique values
0 missing
Community_Membership_Religiousnominal2 unique values
0 missing
Disability_Visionnominal2 unique values
0 missing
Community_Membership_Politicalnominal2 unique values
0 missing
Community_Membership_Othernominal2 unique values
0 missing
Community_Membership_Nonenominal2 unique values
0 missing
Community_Membership_Hobbiesnominal2 unique values
0 missing
Community_Membership_Familynominal2 unique values
0 missing
Community_Buildingnominal4 unique values
0 missing
Agenominal77 unique values
0 missing
How_You_Heard_About_Survey_Othersnominal2 unique values
0 missing
Marital_Statusnominal7 unique values
0 missing
Major_Occupationnominal5 unique values
0 missing
Major_Geographical_Locationnominal10 unique values
0 missing
How_You_Heard_About_Survey_WWW_Pagenominal2 unique values
0 missing
How_You_Heard_About_Survey_Usenet_Newsnominal2 unique values
0 missing
How_You_Heard_About_Survey_Search_Enginenominal2 unique values
0 missing
How_You_Heard_About_Survey_Remeberednominal2 unique values
0 missing
How_You_Heard_About_Survey_Printed_Medianominal2 unique values
0 missing
Actual_Timenominal46 unique values
0 missing
How_You_Heard_About_Survey_Mailing_Listnominal2 unique values
0 missing
How_You_Heard_About_Survey_Friendnominal2 unique values
0 missing
How_You_Heard_About_Survey_Bannernominal2 unique values
0 missing
Household_Incomenominal9 unique values
0 missing
Gendernominal2 unique values
0 missing
Falsification_of_Informationnominal7 unique values
0 missing
Education_Attainmentnominal9 unique values
0 missing
Show all 69 features

107 properties

NumberOfInstances
10108
Number of instances (rows) of the dataset.
NumberOfFeatures
69
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
2699
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
2699
Number of instances with at least one value missing.
NumberOfNumericFeatures
0
Number of numeric attributes.
NumberOfSymbolicFeatures
69
Number of nominal attributes.
AutoCorrelation
0.61
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.91
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
0.13
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
0.66
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
0.91
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
0.13
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
0.66
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
0.91
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
0.13
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
0.66
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
0.84
Entropy of the target attribute values.
DecisionStumpAUC
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.27
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.01
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
40.3
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.11
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.11
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.11
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
73.14
Percentage of instances belonging to the most frequent class.
MajorityClassSize
7393
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
5.71
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.38
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
129
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
1
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
Mean of means among attributes of the numeric type.
MeanMutualInformation
0.02
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
47.03
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
8.36
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
0.04
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
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
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
26.86
Percentage of instances belonging to the least frequent class.
MinorityClassSize
2715
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.15
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
49
Number of binary attributes.
PercentageOfBinaryFeatures
71.01
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
26.7
Percentage of instances having missing values.
PercentageOfMissingValues
0.39
Percentage of missing values.
PercentageOfNumericFeatures
0
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
100
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.37
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
0
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
0.64
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
0.98
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.01
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.69
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.69
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.69
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.26
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.29
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.26
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.29
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.26
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.29
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
22.7
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.18
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

17 tasks

Supervised Classification on kdd_internet_usage
343 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Who_Pays_for_Access_Work
Supervised Classification on kdd_internet_usage
209 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Who_Pays_for_Access_Work
Supervised Classification on kdd_internet_usage
0 runs - estimation_procedure: 33% Holdout set - target_feature: Who_Pays_for_Access_Work
Supervised Classification on kdd_internet_usage
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_precision - target_feature: Country
Learning Curve on kdd_internet_usage
70 runs - estimation_procedure: 10-fold Learning Curve - target_feature: Who_Pays_for_Access_Work
Supervised Data Stream Classification on kdd_internet_usage
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: Who_Pays_for_Access_Work
Clustering on kdd_internet_usage
0 runs
Clustering on kdd_internet_usage
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_internet_usage
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_internet_usage
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_internet_usage
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_internet_usage
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_internet_usage
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_internet_usage
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_internet_usage
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_internet_usage
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_internet_usage
0 runs - estimation_procedure: 50 times Clustering
Define a new task