CPC H04W 16/22 (2013.01) [G06N 3/047 (2023.01); H04L 41/145 (2013.01); H04L 41/147 (2013.01); H04L 41/16 (2013.01); H04W 24/02 (2013.01); H04W 24/08 (2013.01)] | 17 Claims |
1. A method, comprising:
receiving a first dimension set;
extracting a first latent feature set from the first dimension set;
training a first base predictor based on the first latent feature set;
generating a second dimension set based on the first dimension set, the second dimension set having fewer dimensions than the first dimension set;
extracting a second latent feature set from the second dimension set;
training a second base predictor based on the second latent feature set; and
generating a traffic prediction based on the first base predictor and the second base predictor,
wherein generating the second dimension set comprises:
sampling each dimension in the first dimension set with a predetermined number of runs; and
determining that dimensions in the first dimension set with a number of occurrences in the predetermined number of runs that is greater than a sampling threshold are to be included in the second dimension set.
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