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Table 1 An average accuracy of four prediction algorithms and theoretical upper bound of predictability calculated for the three types of synthetic sequences

From: Explaining human mobility predictions through a pattern matching algorithm

 

Random [%]

Markovian [%]

Non-stationary [%]

GRU

19.11 ± 18.6

34.46 ± 26.2

23.40 ± 15.2

RF

18.93 ± 18.9

41.01 ± 27.7

25.22 ± 15.5

MC

19.49 ± 18.0

28.29 ± 21.7

23.12 ± 15.2

Toploc

19.54 ± 19.7

13.97 ± 12.4

27.90 ± 16.5

\(\Pi _{\max}\)

40.04 ± 8.6

52.10 ± 15.7

44.05 ± 5.1

  1. GRU is the deep neural network algorithm, RF is an ensemble decision trees method, MC is the Markov chains-based prediction algorithm, and Toploc is a baseline predictor. Bold values indicate the best result for each sequence type. Values given after the plus-minus signs are corresponding standard deviations.