What is one-hot encoding and why is it useful?

What is one-hot encoding and why is it useful?



Way to represent the target variables in classification problems. Target variables are converted from string values ("dog") to one-hot encoded vectors. One-hot encoded vector is filled with 1 at the index at the target class and 0 everywhere else. Makes no assumption of similarity of target variables. Makes multi-class classification possible with softmax.

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