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ldpa

ldpa

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Author: Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Localization+Data+for+Person+Activity) Please cite: B. Kaluza, V. Mirchevska, E. Dovgan, M. Lustrek, M. Gams, An Agent-based Approach to Care in Independent Living, International Joint Conference on Ambient Intelligence (AmI-10), Malaga, Spain, In press Dataset Title: Localization Data for Person Activity Data Set Abstract: Data contains recordings of five people performing different activities. Each person wore four sensors (tags) while performing the same scenario five times. Source: - Creators: Mitja Lustrek (mitja.lustrek '@' ijs.si), Bostjan Kaluza (bostjan.kaluza '@' ijs.si), Rok Piltaver (rok.piltaver '@' ijs.si), Jana Krivec (jana.krivec '@' ijs.si), Vedrana Vidulin (vedrana.vidulin '@' ijs.si) - Jozef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenija - Donor: Bozidara Cvetkovic (boza.cvetkovic '@' ijs.si) - Jozef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenija - Date received: October, 2010 Data Set Information: People used for recording of the data were wearing four tags (ankle left, ankle right, belt and chest). Each instance is a localization data for one of the tags. The tag can be identified by one of the attributes. Attribute Information: Instance example: A01,020-000-033-111,633790226057226795,27.05.2009 14:03:25:723,4.292500972747803,2.0738532543182373,1.36650812625885,walking 1) Sequence Name {A01,A02,A03,A04,A05,B01,B02,B03,B04,B05,C01,C02,C03,C04,C05,D01,D02,D03,D04,D05,E01,E02,E03,E04,E05} (Nominal) - A, B, C, D, E = 5 people 2) Tag identificator {010-000-024-033,020-000-033-111,020-000-032-221,010-000-030-096} (Nominal) - ANKLE_LEFT = 010-000-024-033 - ANKLE_RIGHT = 010-000-030-096 - CHEST = 020-000-033-111 - BELT = 020-000-032-221 3) timestamp (Numeric) all unique 4) date FORMAT = dd.MM.yyyy HH:mm:ss:SSS (Date) 5) x coordinate of the tag (Numeric) 6) y coordinate of the tag (Numeric) 7) z coordinate of the tag (Numeric) 8) activity {walking,falling,'lying down',lying,'sitting down',sitting,'standing up from lying','on all fours','sitting on the ground','standing up from sitting','standing up from sitting on the ground'} (Nominal) Relevant Papers: B. Kaluza, V. Mirchevska, E. Dovgan, M. Lustrek, M. Gams, An Agent-based Approach to Care in Independent Living, International Joint Conference on Ambient Intelligence (AmI-10), Malaga, Spain, In press

8 features

Class (target)nominal11 unique values
0 missing
V1nominal5 unique values
0 missing
V2nominal4 unique values
0 missing
V3numeric164859 unique values
0 missing
V4numeric164834 unique values
0 missing
V5numeric163802 unique values
0 missing
V6numeric163689 unique values
0 missing
V7numeric164482 unique values
0 missing
Show all 8 features

107 properties

NumberOfInstances
164860
Number of instances (rows) of the dataset.
NumberOfFeatures
8
Number of attributes (columns) of the dataset.
NumberOfClasses
11
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
5
Number of numeric attributes.
NumberOfSymbolicFeatures
3
Number of nominal attributes.
AutoCorrelation
1
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.99
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
0.01
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
0.99
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
0.99
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
0.01
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
0.99
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
0.99
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
0.01
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
0.99
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
2.71
Entropy of the target attribute values.
DecisionStumpAUC
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.67
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
407.18
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.18
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.18
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.18
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
33.05
Percentage of instances belonging to the most frequent class.
MajorityClassSize
54480
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
2.3
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
-1.2
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
82429.68
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.01
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
11
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
0
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
47590.87
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
2.15
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
-1.2
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
82188.57
Mean of means among attributes of the numeric type.
MeanMutualInformation
0.01
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
321.75
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
6.67
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
-0
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
47419
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
2
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.2
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
81869.99
Minimum of means among attributes of the numeric type.
MinMutualInformation
0
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
4
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
47224.78
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
0.84
Percentage of instances belonging to the least frequent class.
MinorityClassSize
1381
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.58
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.24
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
0
Number of binary attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
62.5
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
37.5
Percentage of nominal attributes.
Quartile1AttributeEntropy
2
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-1.2
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
81912.93
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
0
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
-0
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
47228.1
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
2.15
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
-1.2
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
82270.72
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.01
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
0
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
47463.95
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
2.3
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
-1.2
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
82423.15
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.01
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
0
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
47587.41
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.2
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.74
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.2
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.74
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.2
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.74
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.17
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.17
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.17
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
3.79
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.26
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.67
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

16 tasks

Supervised Classification on ldpa
6 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
Supervised Classification on ldpa
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
Supervised Classification on ldpa
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: Class
Supervised Classification on ldpa
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Class
Supervised Classification on ldpa
0 runs - estimation_procedure: 4-fold Crossvalidation - target_feature: Class
Clustering on ldpa
0 runs
Clustering on ldpa
0 runs - estimation_procedure: 50 times Clustering
Clustering on ldpa
0 runs - estimation_procedure: 50 times Clustering
Clustering on ldpa
0 runs - estimation_procedure: 50 times Clustering
Clustering on ldpa
0 runs - estimation_procedure: 50 times Clustering
Clustering on ldpa
0 runs - estimation_procedure: 50 times Clustering
Clustering on ldpa
0 runs - estimation_procedure: 50 times Clustering
Clustering on ldpa
0 runs - estimation_procedure: 50 times Clustering
Clustering on ldpa
0 runs - estimation_procedure: 50 times Clustering
Clustering on ldpa
0 runs - estimation_procedure: 50 times Clustering
Clustering on ldpa
0 runs - estimation_procedure: 50 times Clustering
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