Flerskiktsperceptrons
Flerskiktsperceptrons, often abbreviated as MLP, are a class of artificial neural networks. They are distinguished by having at least three layers of nodes: an input layer, one or more hidden layers, and an output layer. Each node in one layer is connected to every node in the next layer, forming a fully connected network. The connections between nodes have associated weights, which are adjusted during the training process.
The process of learning in a flerskiktsperceptron typically involves a supervised learning approach, most commonly using
Flerskiktsperceptrons are capable of approximating any continuous function, a property known as universal approximation. This makes