Classification learner or neural network for supervised learning
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Hi everyone, Beginners question here. I have a problem which I think I can identify as a classification problem which I hope to solve using supervised learning. I've had a good look through Mathworks documentation and elsewhere online in an attempt to answer the following question, without much luck.
Which tool should I use for this type of problem, the classification learner or a neural network from the Neural network toolbox?
My reading of this is that there seems to be some overlap in functionality. If the answer is 'it depends!!' what factors should I look at before choosing...if you have a reference online or in print, great! Thanks very much in advance for your assistance...and patience. regards Kevin
3 Comments
Greg Heath
on 25 May 2016
In order to use a supervised classification NN, you need to train the net on previously classified examples.
If you don't have that, you could cluster (unsupervised classification) the applicants based on scores from different examples within the test.
However, I'm not exactly sure how you would use that info for 2-class classification.
Accepted Answer
Sean de Wolski
on 25 May 2016
Maybe I need to try both and see which works best.
That's what I'd start with.
The next question becomes what are the requirements for your classifier? Is it accuracy? Prediction speed? Ease of interpretation? The things that are answered in the "Choose a classifier" documentation page (which doesn't discuss NN :( ).
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