Ideas for a classification/regression problem.
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Hi,
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.
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Greg Heath
2014-2-28
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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Ilya
2014-2-27
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.
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