Data
delta_elevators

delta_elevators

active ARFF Publicly available Visibility: public Uploaded 23-04-2014 by Jan van Rijn
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Author: Rui Camacho (rcamacho@garfield.fe.up.pt) Source: [Regression datasets collection Luis Torgo](http://www.dcc.fc.up.pt/~ltorgo/Regression/DataSets.html) Please cite: This data set is also obtained from the task of controlling the ailerons of a F16 aircraft, although the target variable and attributes are different from the ailerons domain. The target variable here is a variation instead of an absolute value, and there was some pre-selection of the attributes.

7 features

Se (target)numeric26 unique values
0 missing
climbRatenumeric278 unique values
0 missing
Altitudenumeric20 unique values
0 missing
RollRatenumeric309 unique values
0 missing
curRollnumeric100 unique values
0 missing
diffClbnumeric16 unique values
0 missing
diffDiffClbnumeric6 unique values
0 missing

19 properties

9517
Number of instances (rows) of the dataset.
7
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.
7
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
1
Average class difference between consecutive instances.
100
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
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.

14 tasks

2 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: Se
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: Se
0 runs - estimation_procedure: 33% Holdout set - target_feature: Se
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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