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Multi-Class Classification: Understanding Activation and Loss Functions in Neural Networksby@owlgrey
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Multi-Class Classification: Understanding Activation and Loss Functions in Neural Networks

by Dmitrii Matveichev 25mJanuary 24th, 2024
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To build a multi-class classification neural network you need to use the softmax activation function on its final layer together with cross-entropy loss. The final layer size should be k, where k is the number of classes. The class IDs should be preprocessed with one-hot encoding. Such a neural network will output probabilities p_i that the input belongs to a class i. To find the predicted class ID you need to find the index of the maximum probability.
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