View uci-20070111 kin8nm (public)
- Summary
(No information yet)
- License
- unknown (from Weka repository)
- Dependencies
- Tags
- arff slurped Weka
- Attribute Types
- Floating Point
- Download
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# Instances: 8192 / # Attributes: 9
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- Original Data Format
- arff
- Name
- kin8nm
- Version mldata
- 0
- Comment
This is data set is concerned with the forward kinematics of an 8 link robot arm. Among the existing variants of this data set we have used the variant 8nm, which is known to be highly non-linear and medium noisy.
Original source: DELVE repository of data. Source: collection of regression datasets by Luis Torgo (ltorgo@ncc.up.pt) at http://www.ncc.up.pt/~ltorgo/Regression/DataSets.html Characteristics: 8192 cases, 9 attributes (0 nominal, 9 continuous).
- Names
- theta1,theta2,theta3,theta4,theta5,theta6,theta7,theta8,y,
- Types
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- numeric
- Data (first 10 data points)
theta1 theta2 theta3 theta4 theta5 theta6 theta7 theta8 y -0.01... 0.36... 0.46... 1.30... 0.98... -0.02... 0.66... 0.06... 0.53... 0.36... -0.30... 0.62... -1.44... -0.74... -1.19... -1.03... -0.71... 0.30... 1.56... -1.29... 0.07... 1.43... 1.14... -1.29... 1.56... -0.93... 0.51... 0.19... 0.90... -1.35... -0.08... -0.97... 0.82... -0.85... 0.93... 0.49... 0.65... 0.12... -0.00... 0.64... 0.62... -0.64... 1.31... -0.89... 0.47... 1.51... -0.21... 0.48... 0.56... 1.40... 0.38... 1.49... -1.32... 0.28... -0.42... -0.15... 1.49... -1.16... 1.36... 0.45... 0.78... -0.40... 0.52... 0.04... 1.29... 0.04... 0.12... 0.78... 0.86... -1.34... 0.19... 1.11... 0.22... 0.56... 0.67... 1.45... -0.77... 0.26... -1.30... -0.13... 0.57... 0.25... -0.48... 0.53... -1.07... -0.52... 0.15... 0.55... 0.11... 0.79... ... ... ... ... ... ... ... ... ...
- Description
A gzip'ed tar containing UCI and UCI KDD datasets (uci-20070111.tar.gz, 17,952,832 Bytes)
- URLs
- (No information yet)
- Publications
- Data Source
- http://www.ics.uci.edu/~mlearn/MLRepository.html http://kdd.ics.uci.edu/
- Measurement Details
- Usage Scenario
- revision 1
- by mldata on 2011-09-14 15:35
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Acknowledgements
This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
http://www.pascal-network.org/.