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Table 7 An average proportion of variation of accuracy of predictions made on the synthetic sequences explained by the regression models fit to the evaluated metrics

From: Explaining human mobility predictions through a pattern matching algorithm

 

Random [%]

Markovian [%]

Non-stationary [%]

ESR

91.11

89.98

85.08

SR

78.81

45.81

42.98

DR

78.09

73.85

59.14

ESR + NStationarity

93.03

91.53

83.94

SR + NStationarity

92.08

58.87

81.16

DR + NStationarity

91.55

74.71

81.40

Regularity + Stationarity

91.32

1.25

73.83

GA

91.18

67.41

79.17

GA + NStationarity

93.04

81.56

82.38

IGA

88.12

65.24

75.54

IGA + NStationarity

92.35

77.61

81.78

\(\Pi _{\max}\)

80.76

89.22

76.44

  1. ESR is an equally sparse repeatability, SR is a sparse repeatability, DR is a dense repeatability, GA is a global alignment measure, and IGA is an iterative global alignment measure. All the \(R^{2}\) values are significant at the level of p <0.001. Bold values indicate the best result for each sequence type.