Data
NASA_PHM2008

NASA_PHM2008

active ARFF BSD (from scikit-learn) Visibility: public Uploaded 23-03-2021 by Tan Zheng
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22 features

class (target)numeric357 unique values
0 missing
sensor_1numeric1 unique values
0 missing
sensor_2numeric1574 unique values
0 missing
sensor_3numeric13687 unique values
0 missing
sensor_4numeric16995 unique values
0 missing
sensor_5numeric1 unique values
0 missing
sensor_6numeric3 unique values
0 missing
sensor_7numeric1994 unique values
0 missing
sensor_8numeric856 unique values
0 missing
sensor_9numeric22292 unique values
0 missing
sensor_10numeric2 unique values
0 missing
sensor_11numeric810 unique values
0 missing
sensor_12numeric1615 unique values
0 missing
sensor_13numeric911 unique values
0 missing
sensor_14numeric21585 unique values
0 missing
sensor_15numeric10142 unique values
0 missing
sensor_16numeric2 unique values
0 missing
sensor_17numeric19 unique values
0 missing
sensor_18numeric1 unique values
0 missing
sensor_19numeric1 unique values
0 missing
sensor_20numeric507 unique values
0 missing
sensor_21numeric16978 unique values
0 missing

19 properties

45918
Number of instances (rows) of the dataset.
22
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.
22
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
100
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
-0.99
Average class difference between consecutive instances.
0
Percentage of missing values.

5 tasks

4 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: Mean absolute error - target_feature: class
2 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
1 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean absolute error - target_feature: class
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
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