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steel-plates-fault

steel-plates-fault

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  • Data Science Engineering OpenML-CC18 study_135 study_98 study_99
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Author: Semeion, Research Center of Sciences of Communication, Rome, Italy. Source: [UCI](http://archive.ics.uci.edu/ml/datasets/steel+plates+faults) Please cite: Dataset provided by Semeion, Research Center of Sciences of Communication, Via Sersale 117, 00128, Rome, Italy. __Changes w.r.t. version 1: included one target factor with 7 levels as target variable for the classification. Also deleted the previous 7 binary target variables.__ Steel Plates Faults Data Set A dataset of steel plates' faults, classified into 7 different types. The goal was to train machine learning for automatic pattern recognition. The dataset consists of 27 features describing each fault (location, size, ...) and 1 feature indicating the type of fault (on of 7: Pastry, Z_Scratch, K_Scatch, Stains, Dirtiness, Bumps, Other_Faults). The target is the type of fault. ### Attribute Information * V1: X_Minimum * V2: X_Maximum * V3: Y_Minimum * V4: Y_Maximum * V5: Pixels_Areas * V6: X_Perimeter * V7: Y_Perimeter * V8: Sum_of_Luminosity * V9: Minimum_of_Luminosity * V10: Maximum_of_Luminosity * V11: Length_of_Conveyer * V12: TypeOfSteel_A300 * V13: TypeOfSteel_A400 * V14: Steel_Plate_Thickness * V15: Edges_Index * V16: Empty_Index * V17: Square_Index * V18: Outside_X_Index * V19: Edges_X_Index * V20: Edges_Y_Index * V21: Outside_Global_Index * V22: LogOfAreas * V23: Log_X_Index * V24: Log_Y_Index * V25: Orientation_Index * V26: Luminosity_Index * V27: SigmoidOfAreas * target: 7 types of fault as classification target ### Relevant Papers 1.M Buscema, S Terzi, W Tastle, A New Meta-Classifier,in NAFIPS 2010, Toronto (CANADA),26-28 July 2010, 978-1-4244-7858-6/10 ©2010 IEEE 2.M Buscema, MetaNet: The Theory of Independent Judges, in Substance Use & Misuse, 33(2), 439-461,1998

28 features

target (target)nominal7 unique values
0 missing
V1numeric962 unique values
0 missing
V2numeric994 unique values
0 missing
V3numeric1939 unique values
0 missing
V4numeric1940 unique values
0 missing
V5numeric920 unique values
0 missing
V6numeric399 unique values
0 missing
V7numeric317 unique values
0 missing
V8numeric1909 unique values
0 missing
V9numeric161 unique values
0 missing
V10numeric100 unique values
0 missing
V11numeric84 unique values
0 missing
V12numeric2 unique values
0 missing
V13numeric2 unique values
0 missing
V14numeric24 unique values
0 missing
V15numeric1387 unique values
0 missing
V16numeric1338 unique values
0 missing
V17numeric770 unique values
0 missing
V18numeric454 unique values
0 missing
V19numeric818 unique values
0 missing
V20numeric648 unique values
0 missing
V21numeric3 unique values
0 missing
V22numeric914 unique values
0 missing
V23numeric183 unique values
0 missing
V24numeric217 unique values
0 missing
V25numeric918 unique values
0 missing
V26numeric1522 unique values
0 missing
V27numeric388 unique values
0 missing
Show all 28 features

62 properties

NumberOfInstances
1941
Number of instances (rows) of the dataset.
NumberOfFeatures
28
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
27
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
MeanKurtosisOfNumericAtts
109.59
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
0
Number of binary attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
MeanMeansOfNumericAtts
130102.83
Mean of means among attributes of the numeric type.
Quartile1SkewnessOfNumericAtts
-0.06
First quartile of skewness among attributes of the numeric type.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
Quartile1StdDevOfNumericAtts
0.3
First quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
1
Average class difference between consecutive instances.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
ClassEntropy
2.41
Entropy of the target attribute values.
MeanNominalAttDistinctValues
7
Average number of distinct values among the attributes of the nominal type.
Quartile2KurtosisOfNumericAtts
-0.04
Second quartile (Median) of kurtosis among attributes of the numeric type.
Dimensionality
0.01
Number of attributes divided by the number of instances.
MeanSkewnessOfNumericAtts
3.74
Mean skewness among attributes of the numeric type.
Quartile2MeansOfNumericAtts
1.4
Second quartile (Median) of means among attributes of the numeric type.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MeanStdDevOfNumericAtts
150690.09
Mean standard deviation of attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
MajorityClassPercentage
34.67
Percentage of instances belonging to the most frequent class.
MinAttributeEntropy
Minimal entropy among attributes.
Quartile2SkewnessOfNumericAtts
0.68
Second quartile (Median) of skewness among attributes of the numeric type.
MajorityClassSize
673
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-1.86
Minimum kurtosis among attributes of the numeric type.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
0.5
Second quartile (Median) of standard deviation of attributes of the numeric type.
MaxKurtosisOfNumericAtts
1663.05
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
-0.13
Minimum of means among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
MaxMeansOfNumericAtts
1650738.71
Maximum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
11.36
Third quartile of kurtosis among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
7
The minimal number of distinct values among attributes of the nominal type.
PercentageOfNumericFeatures
96.43
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
571.14
Third quartile of means among attributes of the numeric type.
MaxNominalAttDistinctValues
7
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.93
Minimum skewness among attributes of the numeric type.
PercentageOfSymbolicFeatures
3.57
Percentage of nominal attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
MaxSkewnessOfNumericAtts
39.29
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.06
Minimum standard deviation of attributes of the numeric type.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
2.81
Third quartile of skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
1774590.09
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
2.83
Percentage of instances belonging to the least frequent class.
Quartile1KurtosisOfNumericAtts
-1.15
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
426.48
Third quartile of standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MinorityClassSize
55
Number of instances belonging to the least frequent class.
Quartile1MeansOfNumericAtts
0.57
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Show all 62 properties

16 tasks

Supervised Classification on steel-plates-fault
9051 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: target
Supervised Classification on steel-plates-fault
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: target
Supervised Classification on steel-plates-fault
0 runs - estimation_procedure: 33% Holdout set - target_feature: target
Supervised Classification on steel-plates-fault
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: target
Supervised Classification on steel-plates-fault
0 runs - estimation_procedure: 4-fold Crossvalidation - target_feature: target
Supervised Classification on steel-plates-fault
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: target
Clustering on steel-plates-fault
0 runs - estimation_procedure: 50 times Clustering
Clustering on steel-plates-fault
0 runs - estimation_procedure: 50 times Clustering
Clustering on steel-plates-fault
0 runs - estimation_procedure: 50 times Clustering
Clustering on steel-plates-fault
0 runs - estimation_procedure: 50 times Clustering
Clustering on steel-plates-fault
0 runs
Clustering on steel-plates-fault
0 runs - estimation_procedure: 50 times Clustering
Clustering on steel-plates-fault
0 runs - estimation_procedure: 50 times Clustering
Clustering on steel-plates-fault
0 runs - estimation_procedure: 50 times Clustering
Clustering on steel-plates-fault
0 runs - estimation_procedure: 50 times Clustering
Clustering on steel-plates-fault
0 runs - estimation_procedure: 50 times Clustering
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