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hutsof99_logis

hutsof99_logis

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Author: Source: Unknown - Date unknown Please cite: Graeme D. Hutcheson and Nick Sofroniou 1999 The Multivariate Social Scientist: Introductory Statistics Using Generalized Linear Models. SAGE Publications. Copyright: Graeme D. Hutcheson & Nick Sofroniou, 1999 This software can be freely used for non-commercial purposes and can be freely distributed. Readme file =========== The data sets in this directory are taken from the above book. The data are presented in two formats, *.dat (ascii) and *.por (SPSS portable). The GLIM code and macros are provided in files *.glm and *.mac. Please read the errata file which indicates some minor differences between these data sets and those reported in the book. DATA FILE SOURCE IN BOOK DESCRIPTION Chapter 1 tab1_01.* Table 1.1 Video Games and Hostility Chapter 2 tab2_01.* Table 2.1 Normal Errors tab2_02.* Table 2.2 Skewed Errors tab2_03.* Table 2.3 Curvilinearity Chapter 3 tab3_01.* Table 3.1 Two Simple Models tab3_05.* Table 3.5 Cost and Sound Quality tab3_07.* Table 3.7 Exam marks and College Offers tab3_11.* Table 3.11 Quality of Children's Testimonies Age: 5-6 = 0; 8-9 = 1 Gender: female = 0; male = 1 Location: 1 = home; 2 = school; 3 = police interview 4 = special interview tab3_11d.* Table 3.11 Data in Table 3.11 with indicator dummy codes added Chapter 4 tab4_01.* Table 4.1 Infection Severity and Treatment Outcome Treatment Outcome: 0 = survived 1 = died tab4_14.* Table 4.14 Infection severity, Treatment outcome and Hospital Attended Hospital: 1 = hospital A 2 = hospital B 3 = hospital C tab4.14d.* Table 4.14 Infection severity, Treatment outcome and Hospital Attended including dummy codes logis.* Child witness data: copy of tab3_11, but includes prosecution logis_d.* Child witness data: copy of tab3_11d, but includes prosecution logis.por and logis_d.por provide the data to obtain the parameters calculated in the book (pages 147 to 152). It should be noted that these differ slightly to the parameters obtained using the data sets logis.dat and logis_d.dat, as the *.dat files only record the variable 'coherence' to 2 decimal places. Chapter 5 tab5_01.* Table 5.1 Job Satisfaction for doctors and dentists tab5_04.* Table 5.4 Race, Housing and Illness tab5_07.* Table 5.7 Dopamine and psychosis: integer scoring tab5_08.* Table 5.8 Dopamine and psychosis: mid-ranks scoring tab5_10.* Table 5.10 Treatment and Depression: integer scoring tab5_11.* Table 5.11 Treatment and depression: mid-ranks scoring tab5_13.* Table 5.13 Alcohol consumption and Libido: integer scores tab5_16.* Table 5.16 Alcohol consumption and libido: low vs medium or high tab5_17.* Table 5.17 Alcohol consumption and libido: medium vs high Chapter 6 tab6_11.* Table 6.11 Child witness example data set File: ../data/hutsof99/logis.dat Note: changes from Errata.txt where not included! Information about the dataset CLASSTYPE: numeric CLASSINDEX: none specific

8 features

Quality (target)numeric70 unique values
0 missing
Agenominal2 unique values
0 missing
Gendernominal2 unique values
0 missing
Locationnominal4 unique values
0 missing
Coherencenumeric61 unique values
0 missing
Maturitynumeric61 unique values
0 missing
Delaynumeric50 unique values
0 missing
Prosecutenominal2 unique values
0 missing
Show all 8 features

107 properties

NumberOfInstances
70
Number of instances (rows) of the dataset.
NumberOfFeatures
8
Number of attributes (columns) of the dataset.
NumberOfClasses
0
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
4
Number of nominal attributes.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
RandomTreeDepth1ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MaxNominalAttDistinctValues
4
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.29
Minimum skewness among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3KurtosisOfNumericAtts
-0.26
Third quartile of kurtosis among attributes of the numeric type.
AutoCorrelation
0.18
Average class difference between consecutive instances.
RandomTreeDepth1Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
J48.00001.AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxSkewnessOfNumericAtts
0.24
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.84
Minimum standard deviation of attributes of the numeric type.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3MeansOfNumericAtts
57.15
Third quartile of means among attributes of the numeric type.
CfsSubsetEval_DecisionStumpAUC
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxStdDevOfNumericAtts
25.33
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
PercentageOfNumericFeatures
50
Percentage of numeric attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
CfsSubsetEval_DecisionStumpErrRate
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MeanAttributeEntropy
Average entropy of the attributes.
MinorityClassSize
Number of instances belonging to the least frequent class.
PercentageOfSymbolicFeatures
50
Percentage of nominal attributes.
Quartile3SkewnessOfNumericAtts
0.24
Third quartile of skewness among attributes of the numeric type.
CfsSubsetEval_DecisionStumpKappa
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.0001.AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanKurtosisOfNumericAtts
-0.46
Mean kurtosis among attributes of the numeric type.
NaiveBayesAUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile3StdDevOfNumericAtts
21.76
Third quartile of standard deviation of attributes of the numeric type.
CfsSubsetEval_NaiveBayesAUC
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMeansOfNumericAtts
28.24
Mean of means among attributes of the numeric type.
NaiveBayesErrRate
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1KurtosisOfNumericAtts
-0.75
First quartile of kurtosis among attributes of the numeric type.
REPTreeDepth1AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesErrRate
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
NaiveBayesKappa
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1MeansOfNumericAtts
2.8
First quartile of means among attributes of the numeric type.
REPTreeDepth1ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesKappa
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.001.AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
NumberOfBinaryFeatures
3
Number of binary attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
REPTreeDepth1Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_kNN1NAUC
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
1
Standard deviation of the number of distinct values among attributes of the nominal type.
J48.001.ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNominalAttDistinctValues
2.5
Average number of distinct values among the attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
-0.16
First quartile of skewness among attributes of the numeric type.
REPTreeDepth2AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NErrRate
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
J48.001.Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanSkewnessOfNumericAtts
0.1
Mean skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.84
First quartile of standard deviation of attributes of the numeric type.
REPTreeDepth2ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NKappa
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
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
9.51
Mean standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
REPTreeDepth2Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
ClassEntropy
Entropy of the target attribute values.
kNN1NKappa
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassSize
Number of instances belonging to the most frequent class.
MinAttributeEntropy
Minimal entropy among attributes.
Quartile2KurtosisOfNumericAtts
-0.36
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
24.78
Second quartile (Median) of means among attributes of the numeric type.
REPTreeDepth3AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpAUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxAttributeEntropy
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-0.86
Minimum kurtosis among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
REPTreeDepth3ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpErrRate
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxKurtosisOfNumericAtts
-0.25
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
2.79
Minimum of means among attributes of the numeric type.
Quartile2SkewnessOfNumericAtts
0.22
Second quartile (Median) of skewness among attributes of the numeric type.
REPTreeDepth3Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpKappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxMeansOfNumericAtts
60.61
Maximum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
Quartile2StdDevOfNumericAtts
5.94
Second quartile (Median) of standard deviation of attributes of the numeric type.
RandomTreeDepth1AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Dimensionality
0.11
Number of attributes divided by the number of instances.
MaxMutualInformation
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
37.5
Percentage of binary attributes.
Show all 107 properties

13 tasks

Supervised Regression on hutsof99_logis
2 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: Quality
Supervised Regression on hutsof99_logis
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: Quality
Clustering on hutsof99_logis
0 runs - estimation_procedure: 50 times Clustering
Clustering on hutsof99_logis
0 runs - estimation_procedure: 50 times Clustering
Clustering on hutsof99_logis
0 runs - estimation_procedure: 50 times Clustering
Clustering on hutsof99_logis
0 runs - estimation_procedure: 50 times Clustering
Clustering on hutsof99_logis
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Clustering on hutsof99_logis
0 runs - estimation_procedure: 50 times Clustering
Clustering on hutsof99_logis
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Clustering on hutsof99_logis
0 runs - estimation_procedure: 50 times Clustering
Clustering on hutsof99_logis
0 runs - estimation_procedure: 50 times Clustering
Clustering on hutsof99_logis
0 runs - estimation_procedure: 50 times Clustering
Clustering on hutsof99_logis
0 runs - estimation_procedure: 50 times Clustering
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