Summary

(No information yet)

License

unknown (from Weka repository)

Dependencies

Tags

arff slurped Weka

Attribute Types

Integer,Floating Point,String

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# Instances: 167 / # Attributes: 5
HDF5 (27.5 KB) XML CSV ARFF LibSVM Matlab Octave

Original Data Format

arff

Name

'servo'

Version mldata

0

Comment

1. Title: Servo Data

2. Sources (a) Created by: Karl Ulrich (MIT) in 1986 (b) Donor: Ross Quinlan (c) Date: May 1993

3. Past Usage:

4. Quinlan, J.R., "Learning with continuous classes", Proc. 5th Australian Joint Conference on AI (eds A. Adams and L. Sterling), Singapore: World Scientific, 1992

5. Quinlan, J.R., "Combining instance-based and model-based learning", Proc. ML'93 (ed P.E. Utgoff), San Mateo: Morgan Kaufmann 1993

   Results on 10-way cross-validation:

   Method Average Relative ------ |Err| Error ------- --------

   Guessing mean 1.15 1.00 Instance-based .52 .26 Regression .86 .49 Model trees .45 .29 Neural nets (G. Hinton) .30 .11 Regression+instances .48 .20 Model trees+instances .30 .17 NN+instances .29 .11

6. Relevant Information:

Ross Quinlan:

This data was given to me by Karl Ulrich at MIT in 1986. I didn't record his description at the time, but here's his subsequent (1992) recollection:

 "I seem to remember that the data was from a simulation of a servo
 system involving a servo amplifier, a motor, a lead screw/nut, and a
 sliding carriage of some sort.  It may have been on of the
 translational axes of a robot on the 9th floor of the AI lab.  In any
 case, the output value is almost certainly a rise time, or the time
 required for the system to respond to a step change in a position set
 point."

(Quinlan, ML'93)

"This is an interesting collection of data provided by Karl Ulrich. It covers an extremely non-linear phenomenon - predicting the rise time of a servomechanism in terms of two (continuous) gain settings and two (discrete) choices of mechanical linkages."

1. Number of Instances: 167

2. Number of Attributes: 4 + numeric class attribute

3. Attribute information:

4. motor: A,B,C,D,E

5. screw: A,B,C,D,E

6. pgain: 3,4,5,6

7. vgain: 1,2,3,4,5

8. class: 0.13 to 7.10

9. Missing Attribute Values: None

Names

motor,screw,pgain,vgain,class,

Types

1. nominal:E,B,D,C,A
2. nominal:E,D,A,B,C
3. nominal:5,6,4,3
4. nominal:4,5,3,2,1
5. numeric

Data (first 10 data points)

motor	screw	pgain	vgain	class
E	E	5	4	0.28...
B	D	6	5	0.50...
D	D	4	3	0.35...
B	A	3	2	5.50...
D	B	6	5	0.35...
E	C	4	3	0.80...
C	A	3	2	5.10...
A	A	3	2	5.70...
C	A	6	5	0.76...
D	A	4	1	1.03...
...	...	...	...	...

Description

A jarfile containing 30 regression datasets collected by Luis Torgo (regression-datasets.jar, 10,090,266 Bytes).

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revision 1

by mldata on 2010-11-06 09:57

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