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dbworld-subjects-stemmed

dbworld-subjects-stemmed

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Author: Michele Filannino Source: UCI Please cite: * Dataset: DBworld e-mails data set Task: dbworld-subjects-stemmed * Source: Michele Filannino, PhD University of Manchester Centre for Doctoral Training Email: filannim_AT_cs.man.ac.uk * Data Set Information: I collected 64 e-mails from DBWorld newsletter and I used them to train different algorithms in order to classify between 'announces of conferences' and 'everything else'. I used a binary bag-of-words representation with a stopword removal pre-processing task before. * Attribute Information: Each attribute corresponds to a precise word or stem in the entire data set vocabulary (I used bag-of-words representation). * Relevant Papers: Michele Filannino, 'DBWorld e-mail classification using a very small corpus', Project of Machine Learning course, University of Manchester, 2011.

230 features

Class (target)nominal2 unique values
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V1nominal2 unique values
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V226nominal2 unique values
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V229nominal2 unique values
0 missing
Show first 100 features

107 properties

NumberOfInstances
64
Number of instances (rows) of the dataset.
NumberOfFeatures
230
Number of attributes (columns) of the dataset.
NumberOfClasses
2
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
0
Number of numeric attributes.
NumberOfSymbolicFeatures
230
Number of nominal attributes.
REPTreeDepth1Kappa
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_kNN1NAUC
0.83
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
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
J48.001.ErrRate
0.25
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNominalAttDistinctValues
2
Average number of distinct values among the attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
First quartile of skewness among attributes of the numeric type.
REPTreeDepth2AUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NErrRate
0.22
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
kNN1NAUC
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
J48.001.Kappa
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanSkewnessOfNumericAtts
Mean skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
First quartile of standard deviation of attributes of the numeric type.
REPTreeDepth2ErrRate
0.25
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NKappa
0.57
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
kNN1NErrRate
0.16
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassPercentage
54.69
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
Mean standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
0.12
Second quartile (Median) of entropy among attributes.
REPTreeDepth2Kappa
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
ClassEntropy
0.99
Entropy of the target attribute values.
kNN1NKappa
0.69
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassSize
35
Number of instances belonging to the most frequent class.
MinAttributeEntropy
0.12
Minimal entropy among attributes.
Quartile2KurtosisOfNumericAtts
Second quartile (Median) of kurtosis among attributes of the numeric type.
REPTreeDepth3AUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpAUC
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxAttributeEntropy
0.84
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
Minimum kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
Second quartile (Median) of means among attributes of the numeric type.
REPTreeDepth3ErrRate
0.25
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpErrRate
0.34
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxKurtosisOfNumericAtts
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
Minimum of means among attributes of the numeric type.
Quartile2MutualInformation
0.02
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.
REPTreeDepth3Kappa
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpKappa
0.31
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxMeansOfNumericAtts
Maximum of means among attributes of the numeric type.
MinMutualInformation
0
Minimal mutual information between the nominal attributes and the target attribute.
Quartile2StdDevOfNumericAtts
Second quartile (Median) of standard deviation of attributes of the numeric type.
RandomTreeDepth1AUC
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Dimensionality
3.59
Number of attributes divided by the number of instances.
MaxMutualInformation
0.29
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
PercentageOfBinaryFeatures
100
Percentage of binary attributes.
Quartile3AttributeEntropy
0.2
Third quartile of entropy among attributes.
RandomTreeDepth1ErrRate
0.3
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
EquivalentNumberOfAtts
44.56
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MaxNominalAttDistinctValues
2
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
Minimum skewness among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3KurtosisOfNumericAtts
Third quartile of kurtosis among attributes of the numeric type.
AutoCorrelation
0.94
Average class difference between consecutive instances.
RandomTreeDepth1Kappa
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
J48.00001.AUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxSkewnessOfNumericAtts
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
Minimum standard deviation of attributes of the numeric type.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3MeansOfNumericAtts
Third quartile of means among attributes of the numeric type.
CfsSubsetEval_DecisionStumpAUC
0.83
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
RandomTreeDepth2AUC
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.ErrRate
0.25
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxStdDevOfNumericAtts
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
45.31
Percentage of instances belonging to the least frequent class.
PercentageOfNumericFeatures
0
Percentage of numeric attributes.
Quartile3MutualInformation
0.02
Third quartile of mutual information between the nominal attributes and the target attribute.
CfsSubsetEval_DecisionStumpErrRate
0.22
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
RandomTreeDepth2ErrRate
0.3
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.Kappa
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MeanAttributeEntropy
0.17
Average entropy of the attributes.
MinorityClassSize
29
Number of instances belonging to the least frequent class.
PercentageOfSymbolicFeatures
100
Percentage of nominal attributes.
Quartile3SkewnessOfNumericAtts
Third quartile of skewness among attributes of the numeric type.
CfsSubsetEval_DecisionStumpKappa
0.57
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
RandomTreeDepth2Kappa
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.0001.AUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanKurtosisOfNumericAtts
Mean kurtosis among attributes of the numeric type.
NaiveBayesAUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1AttributeEntropy
0.12
First quartile of entropy among attributes.
Quartile3StdDevOfNumericAtts
Third quartile of standard deviation of attributes of the numeric type.
CfsSubsetEval_NaiveBayesAUC
0.83
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
RandomTreeDepth3AUC
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.ErrRate
0.25
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMeansOfNumericAtts
Mean of means among attributes of the numeric type.
NaiveBayesErrRate
0.27
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1KurtosisOfNumericAtts
First quartile of kurtosis among attributes of the numeric type.
REPTreeDepth1AUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesErrRate
0.22
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
RandomTreeDepth3ErrRate
0.3
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.Kappa
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMutualInformation
0.02
Average mutual information between the nominal attributes and the target attribute.
NaiveBayesKappa
0.44
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1MeansOfNumericAtts
First quartile of means among attributes of the numeric type.
REPTreeDepth1ErrRate
0.25
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesKappa
0.57
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
RandomTreeDepth3Kappa
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.001.AUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNoiseToSignalRatio
6.56
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
NumberOfBinaryFeatures
230
Number of binary attributes.
Quartile1MutualInformation
0.01
First quartile of mutual information between the nominal attributes and the target attribute.
Show all 107 properties

13 tasks

Supervised Classification on dbworld-subjects-stemmed
40 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
Supervised Classification on dbworld-subjects-stemmed
31 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
Clustering on dbworld-subjects-stemmed
0 runs - estimation_procedure: 50 times Clustering
Clustering on dbworld-subjects-stemmed
0 runs - estimation_procedure: 50 times Clustering
Clustering on dbworld-subjects-stemmed
0 runs - estimation_procedure: 50 times Clustering
Clustering on dbworld-subjects-stemmed
0 runs - estimation_procedure: 50 times Clustering
Clustering on dbworld-subjects-stemmed
0 runs - estimation_procedure: 50 times Clustering
Clustering on dbworld-subjects-stemmed
0 runs
Clustering on dbworld-subjects-stemmed
0 runs - estimation_procedure: 50 times Clustering
Clustering on dbworld-subjects-stemmed
0 runs - estimation_procedure: 50 times Clustering
Clustering on dbworld-subjects-stemmed
0 runs - estimation_procedure: 50 times Clustering
Clustering on dbworld-subjects-stemmed
0 runs - estimation_procedure: 50 times Clustering
Clustering on dbworld-subjects-stemmed
0 runs - estimation_procedure: 50 times Clustering
Define a new task