Using MLPregressor to get the confidence vector of MLPclassifier

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1

Dear all

Someone asked on our GitHub if it was possible for FluidMLPClassifier to provide its confidence vector. The answer is that there is another way: since the MLP code is the same under the hood, one can load a model made in the classifier in the regressor and get access to the output vector, in effect a histogram of how much each class is likely to be the right one.

Here it is in Max first - I am using the demo code from the classifier tutorial. I will code the SC version later from the video code again.

classification-video-demo+vector-from-regressor.maxpat (20.2 KB)

2

and here is the SC code. First download the code from the video and run it so you have a classifier working: Classifying Sounds using a Neural Network in SuperCollider - YouTube

then use this and it works mightily!

// import the classifier state as a dictionary
~nn.dump{|i|~nn_dump = i}

// check the content - there is a dictionary called mlp
~nn_dump.post
~nn_dump["mlp"].post

// make a regressor
~reg = FluidMLPRegressor(s)
// load the fitted state
~reg.load(~nn_dump["mlp"])

//check it works
~confidences = Buffer.alloc(s,2);
~realtime_analysis.(~trombone_test);
~realtime_analysis.(~oboe_test);

(
~reg.predictPoint(~mfccbuf, ~confidences, {
	~confidences.getn(0,2,{|i|i.postln});
});
)
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