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Cereals

Cereals

in_preparation ARFF Publicly available Visibility: public Uploaded 07-10-2014 by unknown
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Author: Source: Unknown - Date unknown Please cite: Datasets of Data And Story Library, project illustrating use of basic statistic methods, converted to arff format by Hakan Kjellerstrand. Source: TunedIT: http://tunedit.org/repo/DASL DASL file http://lib.stat.cmu.edu/DASL/Datafiles/Cereals.html Healthy Breakfast Reference: Data available at many grocery stores Authorization: free use Description: Data on several variable of different brands of cereal. A value of -1 for nutrients indicates a missing observation. Number of cases: 77 Variable Names: Name: Name of cereal mfr: Manufacturer of cereal where A = American Home Food Products; G = General Mills; K = Kelloggs; N = Nabisco; P = Post; Q = Quaker Oats; R = Ralston Purina type: cold or hot calories: calories per serving protein: grams of protein fat: grams of fat sodium: milligrams of sodium fiber: grams of dietary fiber carbo: grams of complex carbohydrates sugars: grams of sugars potass: milligrams of potassium vitamins: vitamins and minerals - 0, 25, or 100, indicating the typical percentage of FDA recommended shelf: display shelf (1, 2, or 3, counting from the floor) weight: weight in ounces of one serving cups: number of cups in one serving rating: a rating of the cereals

16 features

mfr (target)nominal7 unique values
0 missing
name (ignore)nominal77 unique values
0 missing
typenominal2 unique values
0 missing
caloriesnumeric11 unique values
0 missing
proteinnumeric6 unique values
0 missing
fatnumeric5 unique values
0 missing
sodiumnumeric27 unique values
0 missing
fibernumeric13 unique values
0 missing
carbonumeric22 unique values
0 missing
sugarsnumeric17 unique values
0 missing
potassnumeric36 unique values
0 missing
vitaminsnumeric3 unique values
0 missing
shelfnumeric3 unique values
0 missing
weightnumeric7 unique values
0 missing
cupsnumeric12 unique values
0 missing
ratingnumeric77 unique values
0 missing
Show all 16 features

107 properties

NumberOfInstances
77
Number of instances (rows) of the dataset.
NumberOfFeatures
16
Number of attributes (columns) of the dataset.
NumberOfClasses
7
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
13
Number of numeric attributes.
NumberOfSymbolicFeatures
3
Number of nominal attributes.
AutoCorrelation
0.33
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.62
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
0.68
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
0.11
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
0.62
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
0.68
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
0.11
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
0.62
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
0.68
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
0.11
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
2.45
Entropy of the target attribute values.
DecisionStumpAUC
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.6
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.21
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
18.76
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.32
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.32
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.32
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
29.87
Percentage of instances belonging to the most frequent class.
MajorityClassSize
23
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
0.24
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
8.65
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
159.68
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.13
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
7
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
2.46
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
83.83
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
0.24
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
2.15
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
35.76
Mean of means among attributes of the numeric type.
MeanMutualInformation
0.13
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
0.82
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
4.5
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
0.57
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
17.34
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
0.24
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.44
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.82
Minimum of means among attributes of the numeric type.
MinMutualInformation
0.13
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
-0.58
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.15
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
1.3
Percentage of instances belonging to the least frequent class.
MinorityClassSize
1
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.68
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.13
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
1
Number of binary attributes.
PercentageOfBinaryFeatures
6.25
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
81.25
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
18.75
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.24
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
0
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
1.59
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
0.13
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
-0.43
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.92
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
0.24
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
1.33
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
6.92
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.13
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
0.31
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
4.28
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
0.24
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
3.9
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
69.37
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.13
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
1.26
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
20.91
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.65
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.57
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.65
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.57
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.65
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.57
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.52
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.52
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.52
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
3.54
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.58
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

14 tasks

Supervised Classification on Cereals
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: mfr
Supervised Classification on Cereals
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: mfr
Supervised Data Stream Classification on Cereals
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: mfr
Clustering on Cereals
0 runs
Clustering on Cereals
0 runs - estimation_procedure: 50 times Clustering
Clustering on Cereals
0 runs - estimation_procedure: 50 times Clustering
Clustering on Cereals
0 runs - estimation_procedure: 50 times Clustering
Clustering on Cereals
0 runs - estimation_procedure: 50 times Clustering
Clustering on Cereals
0 runs - estimation_procedure: 50 times Clustering
Clustering on Cereals
0 runs - estimation_procedure: 50 times Clustering
Clustering on Cereals
0 runs - estimation_procedure: 50 times Clustering
Clustering on Cereals
0 runs - estimation_procedure: 50 times Clustering
Clustering on Cereals
0 runs - estimation_procedure: 50 times Clustering
Clustering on Cereals
0 runs - estimation_procedure: 50 times Clustering
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