I was testing multiple MIR tasks with my pre-trained features from compact_cnn. I thought I was.
It turned out that I didn’t even load the weights file. There is simply no such code. (You’re supposed to laugh at me now. out loud.)
The featured (thumbnail) image is what I ended up doing. Please scroll up and take a look. But I almost never realised it and even wrote quite a lot of ‘discussion’ on the top of the result. (Yeah, laugh at me. LOUDER) Anyway, it means my system was a deep convolutional extreme learning machine.
I couldn’t realised it earlier because the results are quite good. Let’s see how the feature worked with SVM classifier.
Not bad, huh?
A complex pattern-classification problem, cast in a high-dimensional space nonlinearly, is more likely to be linearly separable than in a low-dimensional space, provided that the space is not densely populated.— Cover, T.M., Geometrical and Statistical properties of systems of linear inequalities with applications in pattern recognition, 1965
Still quite interesting. Oh, and the non-ELM results, what I thought I was doing, will be posted to arXiv soon. See you there then.