OpenML

JavaScript is required to properly view the contents of this page!

Explore
- Data
- Task
- Flow
- Run
- Study
- Task type
- Measure
- People
Help
Blog
Contact
Please cite us

sleep

active ARFF Publicly available Visibility: public Uploaded 29-09-2014 by unknown
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes

Issue	#Downvotes for this reason	By

Loading wiki

Help us complete this description Edit

Author: Source: Unknown - Date unknown Please cite: This dataset contains 3 more features compared to version 1 of the same dataset. Data from which conclusions were drawn in the article "Sleep in Mammals: Ecological and Constitutional Correlates" by Allison, T. and Cicchetti, D. (1976), _Science_, November 12, vol. 194, pp. 732-734. Includes brain and body weight, life span, gestation time, time sleeping, and predation and danger indices for 62 mammals. Variables below (from left to right) for Mammals Data Set: species of animal body weight in kg brain weight in g slow wave ("nondreaming") sleep (hrs/day) paradoxical ("dreaming") sleep (hrs/day) total sleep (hrs/day) (sum of slow wave and paradoxical sleep) maximum life span (years) gestation time (days) predation index (1-5) 1 = minimum (least likely to be preyed upon) 5 = maximum (most likely to be preyed upon) sleep exposure index (1-5) 1 = least exposed (e.g. animal sleeps in a well-protected den) 5 = most exposed overall danger index (1-5) (based on the above two indices and other information) 1 = least danger (from other animals) 5 = most danger (from other animals) For more details, see Allison, Truett and Cicchetti, Domenic V. (1976), "Sleep in Mammals: Ecological and Constitutional Correlates", _Science_, November 12, vol. 194, pp. 732-734. The above data set can be freely used for non-commercial purposes and can be freely distributed (permission in writing obtained from Dr. Truett Allison). Submitted by Roger Johnson rwjohnso@silver.sdsmt.edu Information about the dataset CLASSTYPE: numeric CLASSINDEX: none specific

10 features

overall_danger_index (target)	numeric	5 unique values 0 missing
species (ignore)	nominal	62 unique values 0 missing
body_weight	numeric	60 unique values 0 missing
brain_weight	numeric	59 unique values 0 missing
slow_wave	numeric	39 unique values 14 missing
paradoxical	numeric	30 unique values 12 missing
total_sleep	numeric	44 unique values 4 missing
maximum_life_span	numeric	47 unique values 4 missing
gestation_time	numeric	49 unique values 4 missing
predation_index	numeric	5 unique values 0 missing
sleep_exposure_index	numeric	5 unique values 0 missing

Show all 10 features

107 properties

NumberOfInstances

Number of instances (rows) of the dataset.

NumberOfFeatures

Number of attributes (columns) of the dataset.

NumberOfClasses

Number of distinct values of the target attribute (if it is nominal).

NumberOfMissingValues

Number of missing values in the dataset.

NumberOfInstancesWithMissingValues

Number of instances with at least one value missing.

NumberOfNumericFeatures

Number of numeric attributes.

NumberOfSymbolicFeatures

Number of nominal attributes.

AutoCorrelation

-0.48

Average class difference between consecutive instances.

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

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

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

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

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

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

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

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

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

ClassEntropy

Entropy of the target attribute values.

DecisionStumpAUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump

DecisionStumpErrRate

Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump

DecisionStumpKappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump

Dimensionality

0.16

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

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001

J48.00001.ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001

J48.00001.Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001

J48.0001.AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001

J48.0001.ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001

J48.0001.Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

J48.001.AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001

J48.001.ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001

J48.001.Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001

MajorityClassPercentage

Percentage of instances belonging to the most frequent class.

MajorityClassSize

Number of instances belonging to the most frequent class.

MaxAttributeEntropy

Maximum entropy among attributes.

MaxKurtosisOfNumericAtts

45.74

Maximum kurtosis among attributes of the numeric type.

MaxMeansOfNumericAtts

283.13

Maximum of means among attributes of the numeric type.

MaxMutualInformation

Maximum mutual information between the nominal attributes and the target attribute.

MaxNominalAttDistinctValues

The maximum number of distinct values among attributes of the nominal type.

MaxSkewnessOfNumericAtts

6.56

Maximum skewness among attributes of the numeric type.

MaxStdDevOfNumericAtts

930.28

Maximum standard deviation of attributes of the numeric type.

MeanAttributeEntropy

Average entropy of the attributes.

MeanKurtosisOfNumericAtts

7.86

Mean kurtosis among attributes of the numeric type.

MeanMeansOfNumericAtts

67.32

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

Average number of distinct values among the attributes of the nominal type.

MeanSkewnessOfNumericAtts

1.86

Mean skewness among attributes of the numeric type.

MeanStdDevOfNumericAtts

200.87

Mean standard deviation of attributes of the numeric type.

MinAttributeEntropy

Minimal entropy among attributes.

MinKurtosisOfNumericAtts

-1.33

Minimum kurtosis among attributes of the numeric type.

MinMeansOfNumericAtts

1.97

Minimum of means among attributes of the numeric type.

MinMutualInformation

Minimal mutual information between the nominal attributes and the target attribute.

MinNominalAttDistinctValues

The minimal number of distinct values among attributes of the nominal type.

MinSkewnessOfNumericAtts

0.2

Minimum skewness among attributes of the numeric type.

MinStdDevOfNumericAtts

1.44

Minimum standard deviation of attributes of the numeric type.

MinorityClassPercentage

Percentage of instances belonging to the least frequent class.

MinorityClassSize

Number of instances belonging to the least frequent class.

NaiveBayesAUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes

NaiveBayesErrRate

Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes

NaiveBayesKappa

Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes

NumberOfBinaryFeatures

Number of binary attributes.

PercentageOfBinaryFeatures

Percentage of binary attributes.

PercentageOfInstancesWithMissingValues

32.26

Percentage of instances having missing values.

PercentageOfMissingValues

6.13

Percentage of missing values.

PercentageOfNumericFeatures

100

Percentage of numeric attributes.

PercentageOfSymbolicFeatures

Percentage of nominal attributes.

Quartile1AttributeEntropy

First quartile of entropy among attributes.

Quartile1KurtosisOfNumericAtts

-1.2

First quartile of kurtosis among attributes of the numeric type.

Quartile1MeansOfNumericAtts

2.56

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

0.28

First quartile of skewness among attributes of the numeric type.

Quartile1StdDevOfNumericAtts

1.47

First quartile of standard deviation of attributes of the numeric type.

Quartile2AttributeEntropy

Second quartile (Median) of entropy among attributes.

Quartile2KurtosisOfNumericAtts

1.04

Second quartile (Median) of kurtosis among attributes of the numeric type.

Quartile2MeansOfNumericAtts

9.6

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

1.07

Second quartile (Median) of skewness among attributes of the numeric type.

Quartile2StdDevOfNumericAtts

4.14

Second quartile (Median) of standard deviation of attributes of the numeric type.

Quartile3AttributeEntropy

Third quartile of entropy among attributes.

Quartile3KurtosisOfNumericAtts

10.98

Third quartile of kurtosis among attributes of the numeric type.

Quartile3MeansOfNumericAtts

156.46

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

2.78

Third quartile of skewness among attributes of the numeric type.

Quartile3StdDevOfNumericAtts

334.89

Third quartile of standard deviation of attributes of the numeric type.

REPTreeDepth1AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1

REPTreeDepth1ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1

REPTreeDepth1Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1

REPTreeDepth2AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2

REPTreeDepth2ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2

REPTreeDepth2Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2

REPTreeDepth3AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3

REPTreeDepth3ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3

REPTreeDepth3Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3

RandomTreeDepth1AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

RandomTreeDepth1ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

RandomTreeDepth1Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

RandomTreeDepth2AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

RandomTreeDepth2ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

RandomTreeDepth2Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

RandomTreeDepth3AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

RandomTreeDepth3ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

RandomTreeDepth3Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

StdvNominalAttDistinctValues

Standard deviation of the number of distinct values among attributes of the nominal type.

kNN1NAUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk

kNN1NErrRate

Error rate achieved by the landmarker weka.classifiers.lazy.IBk

kNN1NKappa

Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk

Show all 107 properties

13 tasks

Supervised Regression on sleep

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: overall_danger_index

Supervised Regression on sleep

0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: overall_danger_index

Clustering on sleep

0 runs

Clustering on sleep