MLP code with backpropagation training algorithm

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A MLP code with backpropagation training algorithm designed for classification problems.

详 情 说 明

The Multi-Layer Perceptron (MLP) is a type of artificial neural network that has been widely used for classification problems. It is composed of multiple layers of nodes, each of which is connected to the nodes in the previous and next layers. The MLP code with backpropagation training algorithm is one of the most popular implementations of this network. The backpropagation algorithm is used to adjust the weights of the connections between the nodes in order to minimize the error between the predicted and actual outputs. This allows the MLP to learn from the input data and improve its accuracy over time. In summary, the MLP code with backpropagation training algorithm is a powerful tool for solving classification problems with artificial neural networks, providing accurate predictions and allowing for continuous improvement through training.