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blood-transfusion-service-center

blood-transfusion-service-center

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  • OpenML-CC18 OpenML100 study_123 study_135 study_14 study_218 study_34 study_50 study_52 study_7 study_98 study_99 uci study_225 study_236 study_271 study_240 study_253 study_338 study_339 study_342 study_343 study_275
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Author: Prof. I-Cheng Yeh Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Blood+Transfusion+Service+Center) Please cite: Yeh, I-Cheng, Yang, King-Jang, and Ting, Tao-Ming, "Knowledge discovery on RFM model using Bernoulli sequence", Expert Systems with Applications, 2008. Blood Transfusion Service Center Data Set Data taken from the Blood Transfusion Service Center in Hsin-Chu City in Taiwan -- this is a classification problem. To demonstrate the RFMTC marketing model (a modified version of RFM), this study adopted the donor database of Blood Transfusion Service Center in Hsin-Chu City in Taiwan. The center passes their blood transfusion service bus to one university in Hsin-Chu City to gather blood donated about every three months. To build an FRMTC model, we selected 748 donors at random from the donor database. ### Attribute Information * V1: Recency - months since last donation * V2: Frequency - total number of donation * V3: Monetary - total blood donated in c.c. * V4: Time - months since first donation), and a binary variable representing whether he/she donated blood in March 2007 (1 stand for donating blood; 0 stands for not donating blood). The target attribute is a binary variable representing whether he/she donated blood in March 2007 (2 stands for donating blood; 1 stands for not donating blood).

5 features

Class (target)nominal2 unique values
0 missing
V1numeric31 unique values
0 missing
V2numeric33 unique values
0 missing
V3numeric33 unique values
0 missing
V4numeric78 unique values
0 missing
Show all 5 features

107 properties

NumberOfInstances
748
Number of instances (rows) of the dataset.
NumberOfFeatures
5
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
4
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
AutoCorrelation
0.73
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.64
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
0.24
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
0.02
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
0.64
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
0.24
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
0.02
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
0.64
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
0.24
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
0.02
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
0.79
Entropy of the target attribute values.
DecisionStumpAUC
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.24
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
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.22
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.22
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.22
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
76.2
Percentage of instances belonging to the most frequent class.
MajorityClassSize
570
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
15.88
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
1378.68
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
2
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
3.21
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
1459.83
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
10.22
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
356.99
Mean of means among attributes of the numeric type.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
2
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
2.26
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
374.53
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.25
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
5.51
Minimum of means among attributes of the numeric type.
MinMutualInformation
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
0.75
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
5.84
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
23.8
Percentage of instances belonging to the least frequent class.
MinorityClassSize
178
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.24
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.15
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
1
Number of binary attributes.
PercentageOfBinaryFeatures
20
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
80
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
20
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
2.16
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
6.51
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
1.03
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
6.4
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
12.63
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
21.89
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
2.55
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
16.24
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
15.88
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
1042.58
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
3.21
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
1100.96
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.24
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.24
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.24
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.14
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.14
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.14
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0
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
0.29
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

33 tasks

Supervised Classification on blood-transfusion-service-center
387154 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
Supervised Classification on blood-transfusion-service-center
78885 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
Supervised Classification on blood-transfusion-service-center
6 runs - estimation_procedure: 33% Holdout set - target_feature: Class
Supervised Classification on blood-transfusion-service-center
1 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: Class
Supervised Classification on blood-transfusion-service-center
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Class
Supervised Classification on blood-transfusion-service-center
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: area_under_roc_curve - target_feature: Class
Supervised Classification on blood-transfusion-service-center
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: Class
Supervised Classification on blood-transfusion-service-center
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: Class
Supervised Classification on blood-transfusion-service-center
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
Supervised Classification on blood-transfusion-service-center
0 runs - estimation_procedure: 4-fold Crossvalidation - target_feature: Class
Supervised Regression on blood-transfusion-service-center
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: chi-squared - target_feature: V2
Learning Curve on blood-transfusion-service-center
45 runs - estimation_procedure: 10-fold Learning Curve - target_feature: Class
Clustering on blood-transfusion-service-center
0 runs - target_feature: Class
Clustering on blood-transfusion-service-center
0 runs
Clustering on blood-transfusion-service-center
0 runs - estimation_procedure: 50 times Clustering
Clustering on blood-transfusion-service-center
0 runs - estimation_procedure: 50 times Clustering
Clustering on blood-transfusion-service-center
0 runs - target_feature: 2
Clustering on blood-transfusion-service-center
0 runs - estimation_procedure: 50 times Clustering
Clustering on blood-transfusion-service-center
0 runs - estimation_procedure: 50 times Clustering
Clustering on blood-transfusion-service-center
0 runs - estimation_procedure: 50 times Clustering
Clustering on blood-transfusion-service-center
0 runs - estimation_procedure: 50 times Clustering
Clustering on blood-transfusion-service-center
0 runs - estimation_procedure: 50 times Clustering
Clustering on blood-transfusion-service-center
0 runs - estimation_procedure: 50 times Clustering
Clustering on blood-transfusion-service-center
0 runs - estimation_procedure: 50 times Clustering
Clustering on blood-transfusion-service-center
0 runs - estimation_procedure: 50 times Clustering
Subgroup Discovery on blood-transfusion-service-center
1300 runs - target_feature: Class
Subgroup Discovery on blood-transfusion-service-center
1298 runs - target_feature: Class
Subgroup Discovery on blood-transfusion-service-center
0 runs - target_feature: Class
Subgroup Discovery on blood-transfusion-service-center
0 runs - target_feature: Class
Subgroup Discovery on blood-transfusion-service-center
0 runs - target_feature: Class
Subgroup Discovery on blood-transfusion-service-center
0 runs - target_feature: Class
Subgroup Discovery on blood-transfusion-service-center
0 runs - target_feature: Class
Subgroup Discovery on blood-transfusion-service-center
0 runs - target_feature: Class
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