Ideas for a classifica​tion/regre​ssion problem.

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I have some data, like:
X: Car_Weigth, Car_type, Weather_type, Speed_Before_Accident, Drunk_Pilot_Status Y: 1, 2, 3, 4........ 100 miles.
For me, this is a classification problem, easily solved by any classification method, like: 5 inputs for a neural and 100 outputs.
The doubt here, is that, I have 100 classes, and so, what kind of technique can i use to solve this kind of problem ?
any idea would be great.
Greg Heath
Greg Heath on 28 Feb 2014
I don't understand. Please explain and give an example of what you call a class.
fitnet: regression or curve-fitting; NOT temporal prediction
patternnet: classification or pattern-recognition
For the latter case with c classes, the targets should be unit vectors with c-1 zeros and a single one.
timedlaynet, narnet and narxnet: temporal prediction
Use the help and doc commands for details of any function.

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Accepted Answer

Ilya on 27 Feb 2014
You could start with linear regression. If you have the Statistics Toolbox, take a look at LinearModel. Or, if you have an old version of the toolbox, take a look at the regress function. If you don't have the Statistics Toolbox, try the backslash operator \.
For non-parametric regression, you could use decision trees, TreeBagger or fitensemble, all in the Statistics Toolbox. You could use the Neural Network toolbox too.

More Answers (1)

Andre on 28 Feb 2014
Thank you very much.

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