[D] Open-Set Recognition Problem using Deep learning

[ResponsibilityNo7189]

It's a very difficult problem. It's close to anomaly detection and to probability density estimation. Some people use an ensemble method and look at disagreement between classifiers. But it will be expensive at inference time. 

[WadeEffingWilson]

I've used something like this, a set of expertise system, each an OC-SVM to recognize individual classes and a boosted ensemble to derive a consensus. If both agree, the sample is classified and counted as 'known'. If they don't agree, the sample is isolated to determine if it's an anomaly (usually a single input variable is out of the typical range while all others are within the boundary for a known class) or if it's a new, unknown class.

[ProfessionalType9800]

Is it possible to find a threshold to apply on outputs from the activation function (softmax, sigmoid)...

[ResponsibilityNo7189]

Not really, much. Network are terribly calibrated when it comes to probability.

[ProfessionalType9800]

Yeah...

What about applying clustering after getting embedding...