Identifying and predicting social lifestyles in people’s trajectories by neural networks

EPJ Data Science

Table 8 Numbers of trajectories, lifestyles, and POIs as well as the CLSTM accuracy for each of the 38 users

User	# trajectories	# lifestyles	# POIs	CLSTM accuracy
1	1106	14	17	0.53
2	518	14	17	0.34
3	322	14	11	0.46
4	182	12	7	0.48
5	448	13	14	0.54
6	532	14	12	0.55
7	1008	14	18	0.47
8	112	11	8	0.73
9	322	14	10	0.42
10	588	14	19	0.50
11	1092	14	14	0.63
12	1330	14	17	0.57
13	392	12	12	0.53
14	1260	12	7	0.86
15	868	14	15	0.42
16	1008	14	18	0.31
17	434	12	9	0.79
18	280	13	11	0.68
19	1302	14	15	0.70
20	364	14	9	0.57
21	154	14	7	0.27
22	362	14	14	0.59
23	196	14	12	0.43
24	1386	14	20	0.29
25	546	14	12	0.41
26	98	13	6	0.54
27	1498	14	17	0.34
28	210	13	8	0.34
29	378	14	12	0.54
30	140	12	8	0.39
31	1064	14	12	0.64
32	182	14	7	0.48
33	826	14	16	0.43
34	686	13	12	0.65
35	1946	14	22	0.46
36	826	14	13	0.65
37	993	14	14	0.70
38	1190	14	20	0.39