classifier (decoder)

The classifier is the trained model that sits at the end of the pipeline and makes the actual decision. It takes the features extracted from the signal and maps them to a choice — left or right, yes or no, which of several letters — or to a command the device should run. If feature extraction prepares the evidence, the classifier is the judge who weighs it and announces a verdict.

It can be as simple as a straight line drawn through the data. A linear method such as LDA computes a weighted sum of the features and picks one class if the total lands above a threshold and the other if below — fast, robust, and a favourite in real BCIs. At the other end, a neural network can carve up far more tangled boundaries when there is enough training data to support it.

Whatever its form, the classifier has to be trained on labelled examples first, and it is only ever as good as those examples. Because brain signals drift, many systems also report a confidence with each decision, so the interface can hold back or ask again when the model is unsure.