Prediction by Compression

Joel Ratsaby


Statistical prediction, Data compression, Universal sequence prediction


It is well known that text compression can be achieved by predicting the next symbol in the stream of text data based on the history seen up to the current symbol. The better the prediction the more skewed the conditional probability distribution of the next symbol and the shorter the code-word that needs to be assigned to represent this next symbol. What about the opposite direction? Suppose we have a black box that can compress text stream. Can it be used to predict the next symbol in the stream? We introduce a novel criterion based on the length of the compressed data and use it to predict the next symbol. We examine empirically the prediction error rate and its dependency on some compression parameters.

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