Data
internet_usage

internet_usage

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Author: Source: Unknown - Date unknown Please cite: Internet Usage Data Data Type multivariate Abstract This data contains general demographic information on internet users in 1997. Sources Original Owner [1]Graphics, Visualization, & Usability Center College of Computing Geogia Institute of Technology Atlanta, GA Donor [2]Dr Di Cook Department of Statistics Iowa State University Date Donated: June 30, 1999 Data Characteristics This data comes from a survey conducted by the Graphics and Visualization Unit at Georgia Tech October 10 to November 16, 1997. The full details of the survey are available [3]here. The particular subset of the survey provided here is the "general demographics" of internet users. The data have been recoded as entirely numeric, with an index to the codes described in the "Coding" file. The full survey is available from the web site above, along with summaries, tables and graphs of their analyses. In addition there is information on other parts of the survey, including technology demographics and web commerce. Data Format The data is stored in an ASCII files with one observation per line. Spaces separate fields. Past Usage This data was used in the American Statistical Association Statistical Graphics and Computing Sections 1999 Data Exposition. _________________________________________________________________ [4]The UCI KDD Archive [5]Information and Computer Science [6]University of California, Irvine Irvine, CA 92697-3425 Last modified: June 30, 1999 References 1. http://www.gvu.gatech.edu/gvu/user_surveys/survey-1997-10/ 2. http://www.public.iastate.edu/~dicook/ 3. http://www.cc.gatech.edu/gvu/user_surveys/survey-1997-10/ 4. http://kdd.ics.uci.edu/ 5. http://www.ics.uci.edu/ 6. http://www.uci.edu/ Information about the dataset CLASSTYPE: nominal CLASSINDEX: none specific

72 features

Actual_Time (target)nominal46 unique values
0 missing
Agenominal77 unique values
0 missing
Community_Buildingnominal4 unique values
0 missing
Community_Membership_Familynominal2 unique values
0 missing
Community_Membership_Hobbiesnominal2 unique values
0 missing
Community_Membership_Nonenominal2 unique values
0 missing
Community_Membership_Othernominal2 unique values
0 missing
Community_Membership_Politicalnominal2 unique values
0 missing
Community_Membership_Professionalnominal2 unique values
0 missing
Community_Membership_Religiousnominal2 unique values
0 missing
Community_Membership_Supportnominal2 unique values
0 missing
Countrynominal129 unique values
0 missing
Disability_Cognitivenominal2 unique values
0 missing
Disability_Hearingnominal2 unique values
0 missing
Disability_Motornominal2 unique values
0 missing
Disability_Not_Impairednominal2 unique values
0 missing
Disability_Not_Saynominal2 unique values
0 missing
Disability_Visionnominal2 unique values
0 missing
Education_Attainmentnominal9 unique values
0 missing
Falsification_of_Informationnominal7 unique values
0 missing
Gendernominal2 unique values
0 missing
Household_Incomenominal9 unique values
0 missing
How_You_Heard_About_Survey_Bannernominal2 unique values
0 missing
How_You_Heard_About_Survey_Friendnominal2 unique values
0 missing
How_You_Heard_About_Survey_Mailing_Listnominal2 unique values
0 missing
How_You_Heard_About_Survey_Othersnominal2 unique values
0 missing
How_You_Heard_About_Survey_Printed_Medianominal2 unique values
0 missing
How_You_Heard_About_Survey_Remeberednominal2 unique values
0 missing
How_You_Heard_About_Survey_Search_Enginenominal2 unique values
0 missing
How_You_Heard_About_Survey_Usenet_Newsnominal2 unique values
0 missing
How_You_Heard_About_Survey_WWW_Pagenominal2 unique values
0 missing
Major_Geographical_Locationnominal10 unique values
0 missing
Major_Occupationnominal5 unique values
0 missing
Marital_Statusnominal7 unique values
0 missing
Most_Import_Issue_Facing_the_Internetnominal9 unique values
0 missing
Opinions_on_Censorshipnominal4 unique values
0 missing
Primary_Computing_Platformnominal11 unique values
2699 missing
Primary_Languagenominal119 unique values
0 missing
Primary_Place_of_WWW_Accessnominal9 unique values
0 missing
Racenominal8 unique values
0 missing
Not_Purchasing_Bad_experiencenominal2 unique values
0 missing
Not_Purchasing_Bad_pressnominal2 unique values
0 missing
Not_Purchasing_Cant_findnominal2 unique values
0 missing
Not_Purchasing_Company_policynominal2 unique values
0 missing
Not_Purchasing_Easier_locallynominal2 unique values
0 missing
Not_Purchasing_Enough_infonominal2 unique values
0 missing
Not_Purchasing_Judge_qualitynominal2 unique values
0 missing
Not_Purchasing_Never_triednominal2 unique values
0 missing
Not_Purchasing_No_creditnominal2 unique values
0 missing
Not_Purchasing_Not_applicablenominal2 unique values
0 missing
Not_Purchasing_Not_optionnominal2 unique values
0 missing
Not_Purchasing_Othernominal2 unique values
0 missing
Not_Purchasing_Prefer_peoplenominal2 unique values
0 missing
Not_Purchasing_Privacynominal2 unique values
0 missing
Not_Purchasing_Receiptnominal2 unique values
0 missing
Not_Purchasing_Securitynominal2 unique values
0 missing
Not_Purchasing_Too_complicatednominal2 unique values
0 missing
Not_Purchasing_Uncomfortablenominal2 unique values
0 missing
Not_Purchasing_Unfamiliar_vendornominal2 unique values
0 missing
Registered_to_Votenominal4 unique values
0 missing
Sexual_Preferencenominal6 unique values
0 missing
Web_Orderingnominal3 unique values
0 missing
Web_Page_Creationnominal3 unique values
0 missing
Who_Pays_for_Access_Dont_Knownominal2 unique values
0 missing
Who_Pays_for_Access_Othernominal2 unique values
0 missing
Who_Pays_for_Access_Parentsnominal2 unique values
0 missing
Who_Pays_for_Access_Schoolnominal2 unique values
0 missing
Who_Pays_for_Access_Selfnominal2 unique values
0 missing
Who_Pays_for_Access_Worknominal2 unique values
0 missing
Willingness_to_Pay_Feesnominal8 unique values
0 missing
Years_on_Internetnominal5 unique values
0 missing
whonominal10108 unique values
0 missing

107 properties

10108
Number of instances (rows) of the dataset.
72
Number of attributes (columns) of the dataset.
46
Number of distinct values of the target attribute (if it is nominal).
2699
Number of missing values in the dataset.
2699
Number of instances with at least one value missing.
0
Number of numeric attributes.
72
Number of nominal attributes.
6.96
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
49
Number of binary attributes.
0.01
First quartile of mutual information between the nominal attributes and the target attribute.
0.72
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.26
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
0.13
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
148.58
Average number of distinct values among the attributes of the nominal type.
First quartile of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.85
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
1190.47
Standard deviation of the number of distinct values among attributes of the nominal type.
0.54
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
Mean skewness among attributes of the numeric type.
First quartile of standard deviation of attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.57
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
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.36
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
Mean standard deviation of attributes of the numeric type.
0.69
Second quartile (Median) of entropy among attributes.
0.72
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.26
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
0.71
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
28.47
Percentage of instances belonging to the most frequent class.
0.04
Minimal entropy among attributes.
Second quartile (Median) of kurtosis among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
4.18
Entropy of the target attribute values.
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
2878
Number of instances belonging to the most frequent class.
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
13.3
Maximum entropy among attributes.
Minimum of means among attributes of the numeric type.
0.02
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.72
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.58
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum kurtosis among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum of means among attributes of the numeric type.
2
The minimal number of distinct values among attributes of the nominal type.
68.06
Percentage of binary attributes.
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.01
Number of attributes divided by the number of instances.
4.18
Maximum mutual information between the nominal attributes and the target attribute.
Minimum skewness among attributes of the numeric type.
26.7
Percentage of instances having missing values.
0.99
Third quartile of entropy among attributes.
0.69
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
28.68
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
10108
The maximum number of distinct values among attributes of the nominal type.
Minimum standard deviation of attributes of the numeric type.
0.37
Percentage of missing values.
Third quartile of kurtosis among attributes of the numeric type.
0.12
Average class difference between consecutive instances.
0.13
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Maximum skewness among attributes of the numeric type.
0.06
Percentage of instances belonging to the least frequent class.
0
Percentage of numeric attributes.
Third quartile of means among attributes of the numeric type.
0.85
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
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.54
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Maximum standard deviation of attributes of the numeric type.
6
Number of instances belonging to the least frequent class.
100
Percentage of nominal attributes.
0.09
Third quartile of mutual information between the nominal attributes and the target attribute.
0.57
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
0.69
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.36
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.16
Average entropy of the attributes.
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.38
First quartile of entropy among attributes.
Third quartile of skewness among attributes of the numeric type.
0.26
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
0.13
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Mean kurtosis among attributes of the numeric type.
0.55
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of kurtosis among attributes of the numeric type.
Third quartile of standard deviation of attributes of the numeric type.
0.85
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
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.54
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Mean of means among attributes of the numeric type.
0.15
Average mutual information between the nominal attributes and the target attribute.
0.36
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.57
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
0.69
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.36
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

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