View regression-datasets elevators (public)
























- Summary
(No information yet)
- License
- unknown (from Weka repository)
- Dependencies
- Tags
- arff slurped Weka
- Attribute Types
- Integer,Floating Point
- Download
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# Instances: 16599 / # Attributes: 19
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- Original Data Format
- arff
- Name
- elevators
- Version mldata
- 0
- Comment
This data set is also obtained from the task of controlling a F16 aircraft, although the target variable and attributes are different from the ailerons domain. In this case the goal variable is related to an action taken on the elevators of the aircraft.
Characteristics: 8752 cases, 19 continuous attributes Source: collection of regression datasets by Luis Torgo (ltorgo@ncc.up.pt) at http://www.ncc.up.pt/~ltorgo/Regression/DataSets.html Original source: Experiments of Rui Camacho (rcamacho@garfield.fe.up.pt).
- Names
- climbRate,Sgz,p,q,curRoll,absRoll,diffClb,diffRollRate,diffDiffClb,SaTime1,
- Types
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- Data (first 10 data points)
clim... Sgz p q curR... absR... diff... diff... diff... SaTi... ... 118 -55 -0.28 -0.08 -0.2 -11 11 0.005 -0.2 -0.001 ... 390 -45 -0.06 -0.07 -0.6 -12 11 0.01 -0.2 -0.00... ... 68 6 0.11 0.15 0.6 -10 -9 -0.003 -0.2 -0.00... ... -358 -12 -0.2 0.13 -0.3 -11 -7 0.001 -0.1 -0.001 ... -411 -19 -0.18 0.02 -0.5 -11 -3 0.002 1.2 -0.001 ... -374 -29 -0.14 0.03 -0.8 -12 5 0.003 -0.3 -0.00... ... -11 -43 0.34 -0.05 -0.4 -11 9 0.01 -0.2 -0.00... ... 224 5 -0.35 0.06 -1.2 -12 1 0.01 0.2 -0.00... ... -120 13 0.29 0.15 -1.4 -12 -9 0.008 -0.2 -0.00... ... -335 -3 0.27 0.13 -0.1 -11 -8 -0.009 -0.2 -0.001 ... ... ... ... ... ... ... ... ... ... ... ...
- Description
A jarfile containing 30 regression datasets collected by Luis Torgo (regression-datasets.jar, 10,090,266 Bytes).
- URLs
- (No information yet)
- Publications
- Data Source
- Measurement Details
- Usage Scenario
- revision 1
- by mldata on 2010-11-06 09:57
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Acknowledgements
This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
http://www.pascal-network.org/.