Data
libras_move

libras_move

active ARFF Publicly available Visibility: public Uploaded 20-08-2014 by Tobias Kuehn
0 likes downloaded by 4 people , 5 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Author: Daniel Baptista Dias, Sarajane Marques Peres, Helton Hideraldo Biscaro University of Sao Paulo, School of Art, Sciences and Humanities, Sao Paulo, SP, Brazil Source: Unknown - November 2008 Please cite: ### LIBRAS Movement Database LIBRAS, acronym of the Portuguese name "LIngua BRAsileira de Sinais", is the official brazilian sign language. The dataset (movement_libras) contains 15 classes of 24 instances each, where each class references to a hand movement type in LIBRAS. The hand movement is represented as a bidimensional curve performed by the hand in a period of time. The curves were obtained from videos of hand movements, with the Libras performance from 4 different people, during 2 sessions. Each video corresponds to only one hand movement and has about $7$ seconds. Each video corresponds to a function F in a functions space which is the continual version of the input dataset. In the video pre-processing, a time normalization is carried out selecting 45 frames from each video, in according to an uniform distribution. In each frame, the centroid pixels of the segmented objects (the hand) are found, which compose the discrete version of the curve F with 45 points. All curves are normalized in the unitary space. In order to prepare these movements to be analysed by algorithms, we have carried out a mapping operation, that is, each curve F is mapped in a representation with 90 features, with representing the coordinates of movement. Each instance represents 45 points on a bi-dimensional space, which can be plotted in an ordered way (from 1 through 45 as the X coordinate) in order to draw the path of the movement.

91 features

class (target)numeric15 unique values
0 missing
xcoord1numeric214 unique values
0 missing
ycoord1numeric194 unique values
0 missing
xcoord2numeric218 unique values
0 missing
ycoord2numeric189 unique values
0 missing
xcoord3numeric217 unique values
0 missing
ycoord3numeric195 unique values
0 missing
xcoord4numeric216 unique values
0 missing
ycoord4numeric200 unique values
0 missing
xcoord5numeric216 unique values
0 missing
ycoord5numeric193 unique values
0 missing
xcoord6numeric211 unique values
0 missing
ycoord6numeric197 unique values
0 missing
xcoord7numeric217 unique values
0 missing
ycoord7numeric187 unique values
0 missing
xcoord8numeric201 unique values
0 missing
ycoord8numeric194 unique values
0 missing
xcoord9numeric211 unique values
0 missing
ycoord9numeric191 unique values
0 missing
xcoord10numeric217 unique values
0 missing
ycoord10numeric189 unique values
0 missing
xcoord11numeric216 unique values
0 missing
ycoord11numeric190 unique values
0 missing
xcoord12numeric218 unique values
0 missing
ycoord12numeric185 unique values
0 missing
xcoord13numeric219 unique values
0 missing
ycoord13numeric191 unique values
0 missing
xcoord14numeric214 unique values
0 missing
ycoord14numeric186 unique values
0 missing
xcoord15numeric213 unique values
0 missing
ycoord15numeric187 unique values
0 missing
xcoord16numeric218 unique values
0 missing
ycoord16numeric194 unique values
0 missing
xcoord17numeric214 unique values
0 missing
ycoord17numeric184 unique values
0 missing
xcoord18numeric217 unique values
0 missing
ycoord18numeric179 unique values
0 missing
xcoord19numeric213 unique values
0 missing
ycoord19numeric181 unique values
0 missing
xcoord20numeric202 unique values
0 missing
ycoord20numeric184 unique values
0 missing
xcoord21numeric212 unique values
0 missing
ycoord21numeric176 unique values
0 missing
xcoord22numeric207 unique values
0 missing
ycoord22numeric175 unique values
0 missing
xcoord23numeric206 unique values
0 missing
ycoord23numeric179 unique values
0 missing
xcoord24numeric208 unique values
0 missing
ycoord24numeric172 unique values
0 missing
xcoord25numeric213 unique values
0 missing
ycoord25numeric179 unique values
0 missing
xcoord26numeric222 unique values
0 missing
ycoord26numeric182 unique values
0 missing
xcoord27numeric201 unique values
0 missing
ycoord27numeric177 unique values
0 missing
xcoord28numeric210 unique values
0 missing
ycoord28numeric178 unique values
0 missing
xcoord29numeric214 unique values
0 missing
ycoord29numeric182 unique values
0 missing
xcoord30numeric214 unique values
0 missing
ycoord30numeric189 unique values
0 missing
xcoord31numeric214 unique values
0 missing
ycoord31numeric176 unique values
0 missing
xcoord32numeric199 unique values
0 missing
ycoord32numeric184 unique values
0 missing
xcoord33numeric232 unique values
0 missing
ycoord33numeric185 unique values
0 missing
xcoord34numeric219 unique values
0 missing
ycoord34numeric176 unique values
0 missing
xcoord35numeric219 unique values
0 missing
ycoord35numeric182 unique values
0 missing
xcoord36numeric222 unique values
0 missing
ycoord36numeric183 unique values
0 missing
xcoord37numeric227 unique values
0 missing
ycoord37numeric197 unique values
0 missing
xcoord38numeric220 unique values
0 missing
ycoord38numeric192 unique values
0 missing
xcoord39numeric227 unique values
0 missing
ycoord39numeric189 unique values
0 missing
xcoord40numeric222 unique values
0 missing
ycoord40numeric196 unique values
0 missing
xcoord41numeric229 unique values
0 missing
ycoord41numeric196 unique values
0 missing
xcoord42numeric231 unique values
0 missing
ycoord42numeric195 unique values
0 missing
xcoord43numeric225 unique values
0 missing
ycoord43numeric193 unique values
0 missing
xcoord44numeric228 unique values
0 missing
ycoord44numeric211 unique values
0 missing
xcoord45numeric235 unique values
0 missing
ycoord45numeric208 unique values
0 missing

107 properties

360
Number of instances (rows) of the dataset.
91
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
91
Number of numeric attributes.
0
Number of nominal attributes.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
Average number of distinct values among the attributes of the nominal type.
-0.3
First quartile of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Standard deviation of the number of distinct values among attributes of the nominal type.
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
-0.19
Mean skewness among attributes of the numeric type.
0.16
First quartile of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.22
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
-0.7
Second quartile (Median) of kurtosis among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Entropy of the target attribute values.
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Number of instances belonging to the most frequent class.
-1.21
Minimum kurtosis among attributes of the numeric type.
0.51
Second quartile (Median) of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
0.46
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
-0.25
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
-0.24
Second quartile (Median) of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
8
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
0.18
Second quartile (Median) of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.25
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
-0.47
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
The maximum number of distinct values among attributes of the nominal type.
0.14
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
-0.57
Third quartile of kurtosis among attributes of the numeric type.
0.96
Average class difference between consecutive instances.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.19
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
100
Percentage of numeric attributes.
0.53
Third quartile of means among attributes of the numeric type.
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
4.33
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
0
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
-0.04
Third quartile of skewness among attributes of the numeric type.
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
-0.71
Mean kurtosis among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.88
First quartile of kurtosis among attributes of the numeric type.
0.19
Third quartile of standard deviation of attributes of the numeric type.
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.59
Mean of means among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.5
First quartile of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

7 tasks

0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task