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kdd_ipums_la_97-small

kdd_ipums_la_97-small

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Felicia West
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  • binarized binarized_regression_problem mythbusting_1 study_1 study_15 study_20 study_41
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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.

61 features

binaryClass (target)nominal2 unique values
0 missing
marstnominal6 unique values
0 missing
racegnominal7 unique values
0 missing
chbornnominal13 unique values
4283 missing
bplgnominal103 unique values
0 missing
schoolnominal2 unique values
344 missing
educrecnominal9 unique values
344 missing
schltypenominal4 unique values
344 missing
empstatgnominal3 unique values
1772 missing
labforcenominal2 unique values
1772 missing
occ1950nominal191 unique values
3040 missing
occscorenumeric45 unique values
0 missing
seinumeric80 unique values
0 missing
ind1950nominal133 unique values
3040 missing
classwkgnominal2 unique values
3022 missing
wkswork2nominal6 unique values
3625 missing
hrswork2nominal8 unique values
4309 missing
yrlastwknominal7 unique values
4618 missing
workedyrnominal2 unique values
1772 missing
inctotnumeric288 unique values
0 missing
incwagenumeric216 unique values
0 missing
incbusnumeric107 unique values
0 missing
incfarmnumeric18 unique values
0 missing
incssnumeric40 unique values
0 missing
incwelfrnumeric38 unique values
0 missing
incothernumeric101 unique values
0 missing
povertynumeric488 unique values
0 missing
migrat5gnominal7 unique values
576 missing
migplac5nominal98 unique values
6276 missing
movedinnominal8 unique values
0 missing
vetstatnominal2 unique values
4542 missing
poplocnumeric8 unique values
0 missing
gqnominal3 unique values
0 missing
gqtypegnominal8 unique values
0 missing
farmnominal2 unique values
0 missing
ownershgnominal2 unique values
135 missing
valuenumeric12 unique values
0 missing
rentnumeric154 unique values
0 missing
ftotincnumeric409 unique values
0 missing
nfamsnumeric5 unique values
0 missing
ncouplesnumeric4 unique values
0 missing
nmothersnumeric5 unique values
0 missing
nfathersnumeric3 unique values
0 missing
momlocnumeric12 unique values
0 missing
stepmomnumeric4 unique values
0 missing
momrulenumeric6 unique values
0 missing
yearnominal1 unique values
0 missing
steppopnumeric3 unique values
0 missing
poprulenumeric5 unique values
0 missing
splocnumeric8 unique values
0 missing
sprulenumeric5 unique values
0 missing
famsizenumeric15 unique values
0 missing
nchildnumeric10 unique values
0 missing
nchlt5numeric6 unique values
0 missing
famunitnumeric5 unique values
0 missing
eldchnumeric66 unique values
0 missing
yngchnumeric65 unique values
0 missing
nsibsnumeric10 unique values
0 missing
relategnominal13 unique values
0 missing
agenumeric97 unique values
0 missing
sexnominal2 unique values
0 missing
Show all 61 features

107 properties

NumberOfInstances
7019
Number of instances (rows) of the dataset.
NumberOfFeatures
61
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
43814
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
7019
Number of instances with at least one value missing.
NumberOfNumericFeatures
33
Number of numeric attributes.
NumberOfSymbolicFeatures
28
Number of nominal attributes.
AutoCorrelation
0.54
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.97
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
0.04
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
0.92
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
0.97
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
0.04
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
0.92
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
0.97
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
0.04
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
0.92
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
0.95
Entropy of the target attribute values.
DecisionStumpAUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.01
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
5.18
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.04
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.92
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.04
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.92
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.04
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.92
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
63.04
Percentage of instances belonging to the most frequent class.
MajorityClassSize
4425
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
4.36
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
1786.92
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
486783.79
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.69
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
191
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
41.56
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
485340.19
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
1.56
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
65.69
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
48835.09
Mean of means among attributes of the numeric type.
MeanMutualInformation
0.18
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
7.52
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
23.07
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
3.05
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
75319.64
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
-0
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.99
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0
Minimum of means among attributes of the numeric type.
MinMutualInformation
0
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
1
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.89
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.04
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
36.96
Percentage of instances belonging to the least frequent class.
MinorityClassSize
2594
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.3
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.45
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
9
Number of binary attributes.
PercentageOfBinaryFeatures
14.75
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
100
Percentage of instances having missing values.
PercentageOfMissingValues
10.23
Percentage of missing values.
PercentageOfNumericFeatures
54.1
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
45.9
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.88
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-0.7
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
0.63
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
0.51
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.51
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
1.08
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
0.31
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
3.76
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.08
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
1.14
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
2.07
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
2.08
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
11.37
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
25324.53
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.3
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
2.2
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
43338.18
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.04
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.92
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.04
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.92
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.04
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.92
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.1
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.8
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.1
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.8
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.1
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.8
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
47.29
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.07
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.86
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

16 tasks

Supervised Classification on kdd_ipums_la_97-small
476 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
Supervised Classification on kdd_ipums_la_97-small
197 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
Supervised Classification on kdd_ipums_la_97-small
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: binaryClass
Learning Curve on kdd_ipums_la_97-small
71 runs - estimation_procedure: 10-fold Learning Curve - target_feature: binaryClass
Supervised Data Stream Classification on kdd_ipums_la_97-small
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: binaryClass
Clustering on kdd_ipums_la_97-small
0 runs
Clustering on kdd_ipums_la_97-small
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_ipums_la_97-small
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_ipums_la_97-small
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_ipums_la_97-small
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_ipums_la_97-small
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_ipums_la_97-small
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_ipums_la_97-small
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_ipums_la_97-small
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_ipums_la_97-small
0 runs - estimation_procedure: 50 times Clustering
Clustering on kdd_ipums_la_97-small
0 runs - estimation_procedure: 50 times Clustering
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