In [1]:
import pandas as pd
import numpy as np
import seaborn as sns
import src.misc.paths as path
%matplotlib inline
import src.vector_gen.generateTimeInformationVector as gtiv
import src.vector_gen.generate_VectorY as gvy
training_files = "../../dataset/training/"
trajectories_file = "trajectories(table 5)_training.csv"
trajectories_df = pd.read_csv(training_files+trajectories_file)
In [2]:
df_ti = gtiv.generate_timeInformation_df(trajectories_df)
df_y = gvy.generate_VectorY_df(trajectories_df)
df_ti
Out[2]:
weekday
hour
minute
2016-07-19 00:00:00
1
0
0
2016-07-19 02:00:00
1
2
0
2016-07-19 04:00:00
1
4
0
2016-07-19 06:00:00
1
6
0
2016-07-19 08:00:00
1
8
0
2016-07-19 10:00:00
1
10
0
2016-07-19 12:00:00
1
12
0
2016-07-19 14:00:00
1
14
0
2016-07-19 16:00:00
1
16
0
2016-07-19 18:00:00
1
18
0
2016-07-19 20:00:00
1
20
0
2016-07-19 22:00:00
1
22
0
2016-07-20 00:00:00
2
0
0
2016-07-20 02:00:00
2
2
0
2016-07-20 04:00:00
2
4
0
2016-07-20 06:00:00
2
6
0
2016-07-20 08:00:00
2
8
0
2016-07-20 10:00:00
2
10
0
2016-07-20 12:00:00
2
12
0
2016-07-20 14:00:00
2
14
0
2016-07-20 16:00:00
2
16
0
2016-07-20 18:00:00
2
18
0
2016-07-20 20:00:00
2
20
0
2016-07-20 22:00:00
2
22
0
2016-07-21 00:00:00
3
0
0
2016-07-21 02:00:00
3
2
0
2016-07-21 04:00:00
3
4
0
2016-07-21 06:00:00
3
6
0
2016-07-21 08:00:00
3
8
0
2016-07-21 10:00:00
3
10
0
...
...
...
...
2016-10-15 10:00:00
5
10
0
2016-10-15 12:00:00
5
12
0
2016-10-15 14:00:00
5
14
0
2016-10-15 16:00:00
5
16
0
2016-10-15 18:00:00
5
18
0
2016-10-15 20:00:00
5
20
0
2016-10-15 22:00:00
5
22
0
2016-10-16 00:00:00
6
0
0
2016-10-16 02:00:00
6
2
0
2016-10-16 04:00:00
6
4
0
2016-10-16 06:00:00
6
6
0
2016-10-16 08:00:00
6
8
0
2016-10-16 10:00:00
6
10
0
2016-10-16 12:00:00
6
12
0
2016-10-16 14:00:00
6
14
0
2016-10-16 16:00:00
6
16
0
2016-10-16 18:00:00
6
18
0
2016-10-16 20:00:00
6
20
0
2016-10-16 22:00:00
6
22
0
2016-10-17 00:00:00
0
0
0
2016-10-17 02:00:00
0
2
0
2016-10-17 04:00:00
0
4
0
2016-10-17 06:00:00
0
6
0
2016-10-17 08:00:00
0
8
0
2016-10-17 10:00:00
0
10
0
2016-10-17 12:00:00
0
12
0
2016-10-17 14:00:00
0
14
0
2016-10-17 16:00:00
0
16
0
2016-10-17 18:00:00
0
18
0
2016-10-17 20:00:00
0
20
0
1091 rows × 3 columns
In [3]:
df_y
Out[3]:
tw
0
1
...
4
5
routes
A2
A3
B1
B3
C1
C3
A2
A3
B1
B3
...
B1
B3
C1
C3
A2
A3
B1
B3
C1
C3
2016-07-19 00:00:00
46.02
60.06
18.62
70.85
38.50
27.91
58.05
64.30
79.76
148.79
...
176.70
39.41
214.87
16.20
77.74
45.09
9.92
93.72
160.63
8.17
2016-07-19 02:00:00
37.09
35.27
15.58
67.81
8.36
17.12
42.64
77.61
10.38
25.51
...
11.06
31.36
13.87
11.76
39.43
46.12
12.01
98.49
12.14
7.78
2016-07-19 04:00:00
48.13
45.88
9.91
96.67
15.55
9.84
62.11
40.29
94.06
53.15
...
66.98
48.19
30.07
26.15
58.08
70.58
87.83
48.22
67.51
33.00
2016-07-19 06:00:00
46.36
124.66
170.09
145.94
160.38
42.83
48.59
89.85
64.27
127.35
...
73.54
82.63
92.15
236.12
58.97
155.49
69.42
110.50
180.11
60.60
2016-07-19 08:00:00
81.60
137.38
97.06
125.76
151.39
120.73
80.21
165.48
128.75
141.33
...
104.33
127.38
164.52
104.67
69.66
129.28
87.74
117.83
132.77
139.70
2016-07-19 10:00:00
78.31
99.04
132.68
98.92
200.92
139.70
59.41
129.30
170.59
113.00
...
74.90
84.36
195.16
93.07
47.98
86.68
80.95
96.54
182.46
88.35
2016-07-19 12:00:00
60.17
108.74
145.29
144.87
142.74
91.15
49.53
95.43
71.36
136.36
...
140.65
119.37
172.16
180.09
61.13
102.92
99.61
176.65
117.03
140.79
2016-07-19 14:00:00
65.11
96.92
179.98
159.46
147.60
174.84
74.71
101.41
160.78
129.48
...
163.81
129.47
257.20
185.51
58.74
112.32
90.01
120.76
137.86
125.78
2016-07-19 16:00:00
59.64
126.61
78.76
116.07
144.70
183.07
51.97
95.45
105.64
152.50
...
66.65
103.67
192.50
172.78
65.67
102.47
82.13
109.30
141.04
203.77
2016-07-19 18:00:00
85.11
99.14
77.42
108.30
202.21
134.43
50.57
109.12
382.03
91.94
...
62.14
115.99
83.93
219.38
89.64
128.92
115.00
209.49
83.93
90.56
2016-07-19 20:00:00
87.94
113.02
128.65
112.25
164.91
72.64
44.09
105.55
59.01
84.75
...
155.63
133.02
114.64
65.92
51.18
108.17
129.93
96.96
74.71
185.62
2016-07-19 22:00:00
46.09
141.25
35.65
149.31
83.33
51.67
91.85
87.91
37.17
100.55
...
32.59
61.42
28.59
285.82
67.96
85.08
23.50
121.11
35.92
21.77
2016-07-20 00:00:00
46.02
81.05
18.62
50.16
38.50
27.91
37.89
62.65
16.13
45.35
...
20.83
39.41
135.02
16.20
40.75
107.08
9.92
33.25
18.98
8.17
2016-07-20 02:00:00
49.12
35.27
15.58
28.74
8.36
17.12
18.68
82.09
10.38
127.48
...
11.06
104.71
13.87
11.76
100.71
46.12
12.01
148.14
12.14
7.78
2016-07-20 04:00:00
105.65
144.06
9.91
113.72
15.55
9.84
64.32
77.24
30.23
129.63
...
22.54
48.19
30.07
26.15
46.20
151.55
36.27
48.22
67.51
125.32
2016-07-20 06:00:00
44.10
97.48
122.68
112.36
74.69
42.83
59.87
102.50
67.35
386.44
...
98.20
133.20
92.15
424.79
73.68
128.13
94.11
137.98
130.56
175.09
2016-07-20 08:00:00
61.01
140.36
212.31
182.66
237.40
155.16
332.16
192.68
81.16
127.68
...
115.11
142.06
199.87
104.67
23.30
250.81
155.41
170.11
171.96
102.43
2016-07-20 10:00:00
341.79
175.94
107.35
103.82
228.74
221.42
70.14
118.92
91.98
146.52
...
74.90
157.70
117.66
202.93
60.48
107.66
98.20
80.52
125.28
111.24
2016-07-20 12:00:00
53.99
105.16
76.36
111.79
187.53
91.15
49.55
109.57
91.31
47.27
...
89.11
65.45
147.59
123.63
73.50
99.35
231.91
127.10
154.89
164.01
2016-07-20 14:00:00
66.64
115.73
155.33
95.36
147.60
203.20
57.33
112.98
159.89
110.72
...
90.47
134.65
166.11
203.75
70.33
116.61
71.68
174.75
215.74
125.78
2016-07-20 16:00:00
67.11
87.68
144.83
130.69
105.20
159.47
82.79
126.26
80.05
98.28
...
66.65
131.36
125.53
148.84
75.48
123.79
82.13
134.24
175.44
214.36
2016-07-20 18:00:00
67.89
114.30
77.42
101.55
213.84
200.78
85.11
102.69
69.72
113.77
...
62.14
90.80
257.77
131.43
52.10
137.11
52.30
103.43
263.10
234.90
2016-07-20 20:00:00
57.61
116.09
115.93
91.33
205.59
72.64
52.58
113.43
59.01
156.44
...
61.55
86.44
205.68
65.92
68.68
110.21
46.81
111.47
162.60
158.17
2016-07-20 22:00:00
55.45
108.71
121.78
91.52
150.18
185.89
44.94
88.03
37.17
62.19
...
32.59
61.42
167.24
34.71
56.67
80.57
23.50
112.89
35.92
21.77
2016-07-21 00:00:00
39.21
82.98
18.62
85.00
38.50
27.91
36.43
95.15
16.13
45.35
...
20.83
65.78
21.36
16.20
80.25
45.09
9.92
22.18
18.98
8.17
2016-07-21 02:00:00
45.19
35.27
15.58
28.74
8.36
17.12
28.59
35.20
10.38
25.51
...
11.06
31.36
13.87
11.76
83.48
46.12
12.01
29.13
12.14
7.78
2016-07-21 04:00:00
51.53
90.69
9.91
23.75
15.55
9.84
49.89
40.29
93.61
393.05
...
22.54
48.19
30.07
26.15
56.69
133.45
36.27
48.22
67.51
33.00
2016-07-21 06:00:00
63.18
86.80
56.34
166.81
218.35
42.83
87.03
94.82
64.27
136.67
...
73.54
113.78
92.15
72.12
114.72
189.61
99.63
146.58
133.55
60.60
2016-07-21 08:00:00
116.07
160.08
151.02
107.11
125.38
64.31
125.10
151.10
108.87
111.23
...
125.44
119.13
180.06
104.67
88.66
132.49
162.56
108.62
168.40
108.18
2016-07-21 10:00:00
68.50
130.22
151.15
103.82
131.04
100.98
64.06
115.15
91.98
107.04
...
70.34
108.52
175.72
207.92
58.84
79.98
89.66
168.37
147.73
88.35
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
2016-10-15 10:00:00
141.55
479.41
193.03
82.13
130.52
195.73
142.34
225.43
215.81
80.56
...
102.47
99.52
183.99
243.18
51.78
110.14
126.93
125.04
193.78
178.96
2016-10-15 12:00:00
55.49
108.68
148.88
90.00
175.20
91.15
75.10
102.03
194.71
111.61
...
131.88
123.81
311.30
211.62
76.85
107.19
322.43
94.48
345.66
210.76
2016-10-15 14:00:00
70.85
101.44
369.30
147.15
480.54
131.23
68.73
129.67
132.41
112.88
...
99.66
72.51
226.76
200.01
64.57
105.97
166.30
131.37
220.01
195.49
2016-10-15 16:00:00
62.82
186.11
131.17
120.68
183.74
173.84
55.51
136.59
187.96
156.38
...
118.43
143.56
288.68
201.31
56.20
131.52
208.65
116.47
156.18
176.67
2016-10-15 18:00:00
69.84
140.16
117.03
92.53
208.13
95.01
61.47
107.73
113.36
39.24
...
62.14
104.38
174.08
79.10
54.73
116.60
121.98
76.71
83.93
187.67
2016-10-15 20:00:00
49.56
113.54
131.56
81.32
90.82
557.39
71.34
85.96
92.39
73.55
...
61.55
75.68
160.54
127.78
61.11
85.04
152.00
81.70
181.06
57.90
2016-10-15 22:00:00
56.07
98.05
150.00
81.24
208.41
51.67
32.25
82.48
134.46
100.07
...
164.11
137.85
28.59
127.32
59.24
91.96
88.84
94.80
142.51
21.77
2016-10-16 00:00:00
59.43
60.06
18.62
71.69
38.50
176.72
45.70
300.65
93.32
45.35
...
20.83
53.37
21.36
16.20
27.07
45.09
9.92
22.18
18.98
8.17
2016-10-16 02:00:00
91.74
35.27
15.58
12.09
8.36
17.12
36.26
35.20
10.38
25.51
...
11.06
206.38
13.87
11.76
54.07
126.42
12.01
29.13
12.14
7.78
2016-10-16 04:00:00
45.65
28.72
9.91
23.75
15.55
9.84
42.17
40.29
30.23
35.97
...
22.54
86.44
114.24
26.15
44.47
94.31
36.27
48.22
285.05
33.00
2016-10-16 06:00:00
44.35
107.90
56.34
62.56
74.69
42.83
43.37
97.01
64.27
90.34
...
112.56
94.86
137.52
72.12
49.07
101.45
116.25
105.92
186.40
189.78
2016-10-16 08:00:00
65.10
114.11
112.75
93.91
166.49
64.31
78.61
135.07
102.82
98.29
...
121.36
80.88
177.79
141.18
66.83
227.94
97.21
94.94
165.23
181.15
2016-10-16 10:00:00
72.15
171.94
103.33
54.65
210.89
124.70
70.30
132.77
124.10
79.78
...
149.32
59.31
144.38
103.01
55.31
95.59
80.95
126.53
440.99
227.12
2016-10-16 12:00:00
64.06
93.59
134.29
100.55
266.24
152.97
54.81
95.45
143.35
102.87
...
112.56
99.43
195.02
230.93
79.16
183.45
132.12
111.54
201.60
201.56
2016-10-16 14:00:00
52.68
175.09
149.55
103.92
253.72
190.71
60.43
118.46
91.03
128.19
...
128.09
135.54
234.90
209.33
66.86
85.67
120.06
106.91
210.66
286.61
2016-10-16 16:00:00
72.75
168.21
133.51
103.95
264.98
235.16
71.52
164.68
172.85
97.74
...
153.68
117.52
226.31
215.28
93.63
93.54
183.33
110.75
180.95
224.67
2016-10-16 18:00:00
63.15
135.56
117.24
110.04
241.96
141.09
70.38
128.98
69.72
104.61
...
160.60
68.83
269.18
156.06
68.37
94.52
52.30
104.63
202.09
190.96
2016-10-16 20:00:00
64.10
123.63
120.15
87.52
164.39
153.81
54.89
104.32
112.66
90.29
...
106.95
81.92
224.93
65.92
357.05
105.93
110.85
78.72
74.71
57.90
2016-10-16 22:00:00
64.01
103.64
35.65
106.78
183.47
51.67
58.27
105.03
37.17
62.19
...
80.86
61.42
28.59
34.71
52.26
84.51
23.50
90.29
35.92
21.77
2016-10-17 00:00:00
59.61
89.41
95.71
70.85
38.50
27.91
40.03
77.48
16.13
125.27
...
106.77
88.43
21.36
16.20
27.07
45.09
9.92
22.18
18.98
8.17
2016-10-17 02:00:00
37.09
35.27
15.58
28.74
8.36
17.12
51.25
35.20
10.38
25.51
...
11.06
93.78
13.87
11.76
47.24
46.12
12.01
29.13
12.14
7.78
2016-10-17 04:00:00
56.49
91.66
9.91
73.25
15.55
9.84
69.42
126.47
30.23
35.97
...
22.54
48.19
30.07
26.15
45.24
72.77
135.14
113.93
67.51
33.00
2016-10-17 06:00:00
43.74
68.25
56.34
83.62
196.30
42.83
48.09
140.63
75.72
43.62
...
73.54
69.52
224.46
72.12
72.16
171.10
136.97
110.83
168.88
60.60
2016-10-17 08:00:00
133.58
306.58
108.63
147.11
165.10
64.31
108.33
296.26
115.41
118.52
...
108.23
149.29
151.34
104.67
53.21
128.11
122.42
120.32
265.43
218.18
2016-10-17 10:00:00
64.87
118.49
161.91
129.52
142.21
220.20
76.01
132.14
88.98
50.23
...
102.55
102.44
153.59
93.07
44.09
98.61
100.05
109.67
172.90
88.35
2016-10-17 12:00:00
65.24
99.45
131.03
94.10
167.98
104.38
45.44
104.89
104.69
77.63
...
111.03
84.63
218.76
169.18
64.32
93.51
134.56
81.00
165.84
149.21
2016-10-17 14:00:00
52.28
84.48
99.41
98.19
191.14
131.23
70.19
100.53
147.23
104.86
...
138.69
82.67
134.58
124.07
71.70
131.03
76.92
126.84
483.07
125.78
2016-10-17 16:00:00
53.86
109.92
134.99
115.47
180.28
171.02
69.77
111.73
136.45
100.27
...
130.78
118.25
170.14
122.02
53.69
125.55
177.36
102.55
132.85
107.45
2016-10-17 18:00:00
65.40
158.01
77.42
102.74
267.11
173.74
48.66
115.05
98.47
83.02
...
62.14
91.64
83.93
79.10
65.93
86.11
99.04
96.84
188.23
187.43
2016-10-17 20:00:00
52.66
101.30
62.67
99.77
90.82
209.32
72.69
137.58
172.53
84.75
...
61.55
61.96
121.61
159.44
39.55
100.03
46.81
73.88
74.71
57.90
1091 rows × 36 columns
In [4]:
df_all = df_ti.join(df_y)
df_all
C:\Anaconda3\lib\site-packages\pandas\tools\merge.py:205: UserWarning: merging between different levels can give an unintended result (1 levels on the left, 2 on the right)
warnings.warn(msg, UserWarning)
Out[4]:
weekday
hour
minute
(0, A2)
(0, A3)
(0, B1)
(0, B3)
(0, C1)
(0, C3)
(1, A2)
...
(4, B1)
(4, B3)
(4, C1)
(4, C3)
(5, A2)
(5, A3)
(5, B1)
(5, B3)
(5, C1)
(5, C3)
2016-07-19 00:00:00
1
0
0
46.02
60.06
18.62
70.85
38.50
27.91
58.05
...
176.70
39.41
214.87
16.20
77.74
45.09
9.92
93.72
160.63
8.17
2016-07-19 02:00:00
1
2
0
37.09
35.27
15.58
67.81
8.36
17.12
42.64
...
11.06
31.36
13.87
11.76
39.43
46.12
12.01
98.49
12.14
7.78
2016-07-19 04:00:00
1
4
0
48.13
45.88
9.91
96.67
15.55
9.84
62.11
...
66.98
48.19
30.07
26.15
58.08
70.58
87.83
48.22
67.51
33.00
2016-07-19 06:00:00
1
6
0
46.36
124.66
170.09
145.94
160.38
42.83
48.59
...
73.54
82.63
92.15
236.12
58.97
155.49
69.42
110.50
180.11
60.60
2016-07-19 08:00:00
1
8
0
81.60
137.38
97.06
125.76
151.39
120.73
80.21
...
104.33
127.38
164.52
104.67
69.66
129.28
87.74
117.83
132.77
139.70
2016-07-19 10:00:00
1
10
0
78.31
99.04
132.68
98.92
200.92
139.70
59.41
...
74.90
84.36
195.16
93.07
47.98
86.68
80.95
96.54
182.46
88.35
2016-07-19 12:00:00
1
12
0
60.17
108.74
145.29
144.87
142.74
91.15
49.53
...
140.65
119.37
172.16
180.09
61.13
102.92
99.61
176.65
117.03
140.79
2016-07-19 14:00:00
1
14
0
65.11
96.92
179.98
159.46
147.60
174.84
74.71
...
163.81
129.47
257.20
185.51
58.74
112.32
90.01
120.76
137.86
125.78
2016-07-19 16:00:00
1
16
0
59.64
126.61
78.76
116.07
144.70
183.07
51.97
...
66.65
103.67
192.50
172.78
65.67
102.47
82.13
109.30
141.04
203.77
2016-07-19 18:00:00
1
18
0
85.11
99.14
77.42
108.30
202.21
134.43
50.57
...
62.14
115.99
83.93
219.38
89.64
128.92
115.00
209.49
83.93
90.56
2016-07-19 20:00:00
1
20
0
87.94
113.02
128.65
112.25
164.91
72.64
44.09
...
155.63
133.02
114.64
65.92
51.18
108.17
129.93
96.96
74.71
185.62
2016-07-19 22:00:00
1
22
0
46.09
141.25
35.65
149.31
83.33
51.67
91.85
...
32.59
61.42
28.59
285.82
67.96
85.08
23.50
121.11
35.92
21.77
2016-07-20 00:00:00
2
0
0
46.02
81.05
18.62
50.16
38.50
27.91
37.89
...
20.83
39.41
135.02
16.20
40.75
107.08
9.92
33.25
18.98
8.17
2016-07-20 02:00:00
2
2
0
49.12
35.27
15.58
28.74
8.36
17.12
18.68
...
11.06
104.71
13.87
11.76
100.71
46.12
12.01
148.14
12.14
7.78
2016-07-20 04:00:00
2
4
0
105.65
144.06
9.91
113.72
15.55
9.84
64.32
...
22.54
48.19
30.07
26.15
46.20
151.55
36.27
48.22
67.51
125.32
2016-07-20 06:00:00
2
6
0
44.10
97.48
122.68
112.36
74.69
42.83
59.87
...
98.20
133.20
92.15
424.79
73.68
128.13
94.11
137.98
130.56
175.09
2016-07-20 08:00:00
2
8
0
61.01
140.36
212.31
182.66
237.40
155.16
332.16
...
115.11
142.06
199.87
104.67
23.30
250.81
155.41
170.11
171.96
102.43
2016-07-20 10:00:00
2
10
0
341.79
175.94
107.35
103.82
228.74
221.42
70.14
...
74.90
157.70
117.66
202.93
60.48
107.66
98.20
80.52
125.28
111.24
2016-07-20 12:00:00
2
12
0
53.99
105.16
76.36
111.79
187.53
91.15
49.55
...
89.11
65.45
147.59
123.63
73.50
99.35
231.91
127.10
154.89
164.01
2016-07-20 14:00:00
2
14
0
66.64
115.73
155.33
95.36
147.60
203.20
57.33
...
90.47
134.65
166.11
203.75
70.33
116.61
71.68
174.75
215.74
125.78
2016-07-20 16:00:00
2
16
0
67.11
87.68
144.83
130.69
105.20
159.47
82.79
...
66.65
131.36
125.53
148.84
75.48
123.79
82.13
134.24
175.44
214.36
2016-07-20 18:00:00
2
18
0
67.89
114.30
77.42
101.55
213.84
200.78
85.11
...
62.14
90.80
257.77
131.43
52.10
137.11
52.30
103.43
263.10
234.90
2016-07-20 20:00:00
2
20
0
57.61
116.09
115.93
91.33
205.59
72.64
52.58
...
61.55
86.44
205.68
65.92
68.68
110.21
46.81
111.47
162.60
158.17
2016-07-20 22:00:00
2
22
0
55.45
108.71
121.78
91.52
150.18
185.89
44.94
...
32.59
61.42
167.24
34.71
56.67
80.57
23.50
112.89
35.92
21.77
2016-07-21 00:00:00
3
0
0
39.21
82.98
18.62
85.00
38.50
27.91
36.43
...
20.83
65.78
21.36
16.20
80.25
45.09
9.92
22.18
18.98
8.17
2016-07-21 02:00:00
3
2
0
45.19
35.27
15.58
28.74
8.36
17.12
28.59
...
11.06
31.36
13.87
11.76
83.48
46.12
12.01
29.13
12.14
7.78
2016-07-21 04:00:00
3
4
0
51.53
90.69
9.91
23.75
15.55
9.84
49.89
...
22.54
48.19
30.07
26.15
56.69
133.45
36.27
48.22
67.51
33.00
2016-07-21 06:00:00
3
6
0
63.18
86.80
56.34
166.81
218.35
42.83
87.03
...
73.54
113.78
92.15
72.12
114.72
189.61
99.63
146.58
133.55
60.60
2016-07-21 08:00:00
3
8
0
116.07
160.08
151.02
107.11
125.38
64.31
125.10
...
125.44
119.13
180.06
104.67
88.66
132.49
162.56
108.62
168.40
108.18
2016-07-21 10:00:00
3
10
0
68.50
130.22
151.15
103.82
131.04
100.98
64.06
...
70.34
108.52
175.72
207.92
58.84
79.98
89.66
168.37
147.73
88.35
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
2016-10-15 10:00:00
5
10
0
141.55
479.41
193.03
82.13
130.52
195.73
142.34
...
102.47
99.52
183.99
243.18
51.78
110.14
126.93
125.04
193.78
178.96
2016-10-15 12:00:00
5
12
0
55.49
108.68
148.88
90.00
175.20
91.15
75.10
...
131.88
123.81
311.30
211.62
76.85
107.19
322.43
94.48
345.66
210.76
2016-10-15 14:00:00
5
14
0
70.85
101.44
369.30
147.15
480.54
131.23
68.73
...
99.66
72.51
226.76
200.01
64.57
105.97
166.30
131.37
220.01
195.49
2016-10-15 16:00:00
5
16
0
62.82
186.11
131.17
120.68
183.74
173.84
55.51
...
118.43
143.56
288.68
201.31
56.20
131.52
208.65
116.47
156.18
176.67
2016-10-15 18:00:00
5
18
0
69.84
140.16
117.03
92.53
208.13
95.01
61.47
...
62.14
104.38
174.08
79.10
54.73
116.60
121.98
76.71
83.93
187.67
2016-10-15 20:00:00
5
20
0
49.56
113.54
131.56
81.32
90.82
557.39
71.34
...
61.55
75.68
160.54
127.78
61.11
85.04
152.00
81.70
181.06
57.90
2016-10-15 22:00:00
5
22
0
56.07
98.05
150.00
81.24
208.41
51.67
32.25
...
164.11
137.85
28.59
127.32
59.24
91.96
88.84
94.80
142.51
21.77
2016-10-16 00:00:00
6
0
0
59.43
60.06
18.62
71.69
38.50
176.72
45.70
...
20.83
53.37
21.36
16.20
27.07
45.09
9.92
22.18
18.98
8.17
2016-10-16 02:00:00
6
2
0
91.74
35.27
15.58
12.09
8.36
17.12
36.26
...
11.06
206.38
13.87
11.76
54.07
126.42
12.01
29.13
12.14
7.78
2016-10-16 04:00:00
6
4
0
45.65
28.72
9.91
23.75
15.55
9.84
42.17
...
22.54
86.44
114.24
26.15
44.47
94.31
36.27
48.22
285.05
33.00
2016-10-16 06:00:00
6
6
0
44.35
107.90
56.34
62.56
74.69
42.83
43.37
...
112.56
94.86
137.52
72.12
49.07
101.45
116.25
105.92
186.40
189.78
2016-10-16 08:00:00
6
8
0
65.10
114.11
112.75
93.91
166.49
64.31
78.61
...
121.36
80.88
177.79
141.18
66.83
227.94
97.21
94.94
165.23
181.15
2016-10-16 10:00:00
6
10
0
72.15
171.94
103.33
54.65
210.89
124.70
70.30
...
149.32
59.31
144.38
103.01
55.31
95.59
80.95
126.53
440.99
227.12
2016-10-16 12:00:00
6
12
0
64.06
93.59
134.29
100.55
266.24
152.97
54.81
...
112.56
99.43
195.02
230.93
79.16
183.45
132.12
111.54
201.60
201.56
2016-10-16 14:00:00
6
14
0
52.68
175.09
149.55
103.92
253.72
190.71
60.43
...
128.09
135.54
234.90
209.33
66.86
85.67
120.06
106.91
210.66
286.61
2016-10-16 16:00:00
6
16
0
72.75
168.21
133.51
103.95
264.98
235.16
71.52
...
153.68
117.52
226.31
215.28
93.63
93.54
183.33
110.75
180.95
224.67
2016-10-16 18:00:00
6
18
0
63.15
135.56
117.24
110.04
241.96
141.09
70.38
...
160.60
68.83
269.18
156.06
68.37
94.52
52.30
104.63
202.09
190.96
2016-10-16 20:00:00
6
20
0
64.10
123.63
120.15
87.52
164.39
153.81
54.89
...
106.95
81.92
224.93
65.92
357.05
105.93
110.85
78.72
74.71
57.90
2016-10-16 22:00:00
6
22
0
64.01
103.64
35.65
106.78
183.47
51.67
58.27
...
80.86
61.42
28.59
34.71
52.26
84.51
23.50
90.29
35.92
21.77
2016-10-17 00:00:00
0
0
0
59.61
89.41
95.71
70.85
38.50
27.91
40.03
...
106.77
88.43
21.36
16.20
27.07
45.09
9.92
22.18
18.98
8.17
2016-10-17 02:00:00
0
2
0
37.09
35.27
15.58
28.74
8.36
17.12
51.25
...
11.06
93.78
13.87
11.76
47.24
46.12
12.01
29.13
12.14
7.78
2016-10-17 04:00:00
0
4
0
56.49
91.66
9.91
73.25
15.55
9.84
69.42
...
22.54
48.19
30.07
26.15
45.24
72.77
135.14
113.93
67.51
33.00
2016-10-17 06:00:00
0
6
0
43.74
68.25
56.34
83.62
196.30
42.83
48.09
...
73.54
69.52
224.46
72.12
72.16
171.10
136.97
110.83
168.88
60.60
2016-10-17 08:00:00
0
8
0
133.58
306.58
108.63
147.11
165.10
64.31
108.33
...
108.23
149.29
151.34
104.67
53.21
128.11
122.42
120.32
265.43
218.18
2016-10-17 10:00:00
0
10
0
64.87
118.49
161.91
129.52
142.21
220.20
76.01
...
102.55
102.44
153.59
93.07
44.09
98.61
100.05
109.67
172.90
88.35
2016-10-17 12:00:00
0
12
0
65.24
99.45
131.03
94.10
167.98
104.38
45.44
...
111.03
84.63
218.76
169.18
64.32
93.51
134.56
81.00
165.84
149.21
2016-10-17 14:00:00
0
14
0
52.28
84.48
99.41
98.19
191.14
131.23
70.19
...
138.69
82.67
134.58
124.07
71.70
131.03
76.92
126.84
483.07
125.78
2016-10-17 16:00:00
0
16
0
53.86
109.92
134.99
115.47
180.28
171.02
69.77
...
130.78
118.25
170.14
122.02
53.69
125.55
177.36
102.55
132.85
107.45
2016-10-17 18:00:00
0
18
0
65.40
158.01
77.42
102.74
267.11
173.74
48.66
...
62.14
91.64
83.93
79.10
65.93
86.11
99.04
96.84
188.23
187.43
2016-10-17 20:00:00
0
20
0
52.66
101.30
62.67
99.77
90.82
209.32
72.69
...
61.55
61.96
121.61
159.44
39.55
100.03
46.81
73.88
74.71
57.90
1091 rows × 39 columns
In [5]:
feature_cols = ['hour', 'minute', 'weekday']
y_cols = [('0', 'A2'), ('0', 'A3'),
('0', 'B1'), ('0', 'B3'), ('0', 'C1'), ('0', 'C3'), ('1', 'A2'),
('1', 'A3'), ('1', 'B1'), ('1', 'B3'), ('1', 'C1'), ('1', 'C3'),
('2', 'A2'), ('2', 'A3'), ('2', 'B1'), ('2', 'B3'), ('2', 'C1'),
('2', 'C3'), ('3', 'A2'), ('3', 'A3'), ('3', 'B1'), ('3', 'B3'),
('3', 'C1'), ('3', 'C3'), ('4', 'A2'), ('4', 'A3'), ('4', 'B1'),
('4', 'B3'), ('4', 'C1'), ('4', 'C3'), ('5', 'A2'), ('5', 'A3'),
('5', 'B1'), ('5', 'B3'), ('5', 'C1'), ('5', 'C3')]
In [6]:
sns.pairplot(df_all, x_vars=feature_cols, y_vars=y_cols, size=6, aspect=1.3, kind='reg')
Out[6]:
<seaborn.axisgrid.PairGrid at 0x26198616080>
In [7]:
# not working!?!?!
#import src.misc.split_train_valid as split
#training, validation, testing = split.split_dataset(df_all, train = 0.9, validation = 0.000001)
In [8]:
#from sklearn.model_selection import train_test_split
#x_train, x_test, y_train, y_test = train_test_split(df[feature_cols], df['avg_travel_time'], test_size=0.2, random_state=42)
# k-fold cross validation
# 13 weeks
In [9]:
7*12
Out[9]:
84
In [10]:
# split
train_weeks = 12 # of 13
train_rows = train_weeks*7*12
train = df_all[:train_rows]
test = df_all[train_rows:]
# define
x_train = train[feature_cols]
y_train = train[y_cols]
x_test = test[feature_cols]
y_test = test[y_cols]
In [11]:
y_test
Out[11]:
(0, A2)
(0, A3)
(0, B1)
(0, B3)
(0, C1)
(0, C3)
(1, A2)
(1, A3)
(1, B1)
(1, B3)
...
(4, B1)
(4, B3)
(4, C1)
(4, C3)
(5, A2)
(5, A3)
(5, B1)
(5, B3)
(5, C1)
(5, C3)
2016-10-11 00:00:00
52.28
60.06
18.62
50.16
38.50
27.91
37.07
107.80
16.13
103.27
...
20.83
39.41
21.36
16.20
27.07
45.09
69.89
94.61
18.98
8.17
2016-10-11 02:00:00
37.09
35.27
15.58
28.74
8.36
17.12
52.36
35.20
10.38
75.56
...
11.06
31.36
13.87
11.76
53.40
46.12
99.88
29.13
12.14
7.78
2016-10-11 04:00:00
38.38
45.88
9.91
23.75
15.55
9.84
53.69
40.29
30.23
35.97
...
22.54
48.19
164.07
156.45
41.32
77.45
90.51
48.22
206.02
33.00
2016-10-11 06:00:00
44.41
97.47
125.78
62.56
74.69
42.83
32.56
127.90
96.05
71.58
...
127.86
143.01
158.56
72.12
50.97
137.73
134.92
110.76
173.09
190.27
2016-10-11 08:00:00
68.09
146.16
86.56
142.52
158.31
64.31
75.02
168.43
127.10
93.00
...
120.29
104.09
129.01
202.18
70.26
121.44
93.94
133.37
166.25
117.08
2016-10-11 10:00:00
58.42
134.14
128.12
133.50
241.20
100.98
59.50
122.61
96.85
231.31
...
97.47
93.11
202.58
93.07
72.78
96.14
102.81
102.93
145.38
132.98
2016-10-11 12:00:00
62.17
168.92
140.94
81.62
159.03
206.08
67.42
105.85
134.51
129.76
...
101.64
106.02
188.35
123.63
61.31
122.76
106.54
103.98
198.28
132.72
2016-10-11 14:00:00
63.76
84.14
131.75
160.78
198.61
159.13
70.16
104.73
106.43
110.78
...
120.09
113.49
177.20
124.07
80.86
112.35
107.40
124.56
186.99
151.44
2016-10-11 16:00:00
66.96
102.97
85.30
97.92
151.63
143.58
85.57
100.22
93.09
130.13
...
111.53
103.08
193.29
183.23
67.00
146.57
254.55
76.11
230.08
218.23
2016-10-11 18:00:00
48.92
112.86
204.27
113.66
250.10
95.01
121.45
280.83
126.37
64.97
...
128.57
129.44
160.61
79.10
77.23
115.81
128.59
102.91
170.00
207.18
2016-10-11 20:00:00
88.02
98.23
108.57
95.91
153.19
72.64
53.83
104.47
93.71
84.75
...
61.55
268.29
161.02
122.44
74.66
91.72
350.79
120.55
201.53
218.45
2016-10-11 22:00:00
54.76
95.40
148.41
86.69
162.99
51.67
48.85
97.33
37.17
86.00
...
32.59
136.46
137.63
34.71
50.05
62.06
23.50
39.47
35.92
111.98
2016-10-12 00:00:00
53.89
55.96
18.62
83.32
38.50
27.91
69.38
64.30
16.13
45.35
...
20.83
39.41
21.36
16.20
27.07
67.30
9.92
22.18
18.98
8.17
2016-10-12 02:00:00
35.75
35.27
15.58
28.74
8.36
17.12
57.34
89.27
10.38
105.41
...
11.06
83.37
13.87
11.76
60.73
46.12
12.01
29.13
12.14
7.78
2016-10-12 04:00:00
41.58
82.20
9.91
23.75
15.55
9.84
42.86
40.29
30.23
35.97
...
97.33
87.31
188.20
26.15
58.03
99.03
36.27
48.22
67.51
33.00
2016-10-12 06:00:00
49.68
93.64
100.25
84.28
74.69
42.83
45.53
135.08
64.27
98.94
...
73.54
73.71
92.15
110.15
63.15
138.92
69.42
153.30
143.44
60.60
2016-10-12 08:00:00
86.16
171.63
117.33
84.05
146.38
175.34
83.28
189.11
184.11
156.47
...
132.43
168.48
116.31
104.67
65.32
143.11
87.74
156.67
194.99
215.89
2016-10-12 10:00:00
94.91
131.99
107.56
104.83
121.63
209.00
58.60
99.85
106.44
117.59
...
64.19
76.81
242.19
140.85
57.23
111.28
104.02
110.46
176.85
88.35
2016-10-12 12:00:00
55.71
81.89
120.83
92.75
180.54
174.42
61.98
100.87
82.99
26.74
...
132.50
103.32
142.53
176.53
64.27
112.77
85.15
103.29
139.48
160.53
2016-10-12 14:00:00
71.25
105.32
113.41
92.04
172.53
115.48
62.77
109.13
142.55
87.21
...
96.16
81.32
221.58
218.83
50.12
99.73
143.76
95.90
151.01
141.39
2016-10-12 16:00:00
60.51
97.40
126.86
86.15
153.51
170.92
57.58
83.99
111.50
111.87
...
66.65
93.10
172.73
148.58
78.55
114.99
110.97
103.29
171.72
196.05
2016-10-12 18:00:00
81.69
113.32
127.47
160.28
186.11
146.06
52.32
112.96
132.60
87.50
...
62.14
102.74
169.59
203.03
67.94
101.71
52.30
51.49
196.28
90.56
2016-10-12 20:00:00
76.01
100.00
89.78
82.10
183.10
72.64
57.85
110.36
130.23
113.44
...
96.42
97.17
162.05
65.92
66.46
89.55
46.81
98.05
74.71
57.90
2016-10-12 22:00:00
58.35
112.08
35.65
68.51
156.96
51.67
35.44
46.24
96.12
71.62
...
99.06
80.30
112.53
34.71
42.57
56.12
23.50
121.04
35.92
21.77
2016-10-13 00:00:00
74.92
60.06
18.62
50.16
38.50
27.91
46.58
91.02
16.13
45.35
...
20.83
39.41
21.36
16.20
50.53
45.09
94.23
22.18
18.98
97.82
2016-10-13 02:00:00
129.60
93.48
15.58
28.74
145.63
17.12
52.09
95.52
10.38
25.51
...
68.08
31.36
13.87
11.76
73.72
46.12
12.01
29.13
12.14
7.78
2016-10-13 04:00:00
54.43
73.95
9.91
23.75
142.71
9.84
57.76
106.28
100.69
35.97
...
22.54
107.66
30.07
26.15
37.66
87.00
36.27
95.92
67.51
33.00
2016-10-13 06:00:00
54.31
121.44
119.71
62.56
127.55
42.83
77.89
92.64
138.09
83.66
...
140.66
16.85
92.15
119.28
87.81
114.64
102.54
106.15
214.35
212.35
2016-10-13 08:00:00
82.59
176.52
117.33
113.20
169.92
194.72
85.20
105.61
119.43
82.62
...
109.39
67.84
176.34
104.67
67.78
96.76
146.40
107.55
152.02
187.55
2016-10-13 10:00:00
65.09
105.11
137.43
82.42
182.90
159.94
61.71
119.30
121.10
117.33
...
178.25
110.95
149.97
93.07
53.17
144.99
107.04
104.34
134.46
137.87
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
2016-10-15 10:00:00
141.55
479.41
193.03
82.13
130.52
195.73
142.34
225.43
215.81
80.56
...
102.47
99.52
183.99
243.18
51.78
110.14
126.93
125.04
193.78
178.96
2016-10-15 12:00:00
55.49
108.68
148.88
90.00
175.20
91.15
75.10
102.03
194.71
111.61
...
131.88
123.81
311.30
211.62
76.85
107.19
322.43
94.48
345.66
210.76
2016-10-15 14:00:00
70.85
101.44
369.30
147.15
480.54
131.23
68.73
129.67
132.41
112.88
...
99.66
72.51
226.76
200.01
64.57
105.97
166.30
131.37
220.01
195.49
2016-10-15 16:00:00
62.82
186.11
131.17
120.68
183.74
173.84
55.51
136.59
187.96
156.38
...
118.43
143.56
288.68
201.31
56.20
131.52
208.65
116.47
156.18
176.67
2016-10-15 18:00:00
69.84
140.16
117.03
92.53
208.13
95.01
61.47
107.73
113.36
39.24
...
62.14
104.38
174.08
79.10
54.73
116.60
121.98
76.71
83.93
187.67
2016-10-15 20:00:00
49.56
113.54
131.56
81.32
90.82
557.39
71.34
85.96
92.39
73.55
...
61.55
75.68
160.54
127.78
61.11
85.04
152.00
81.70
181.06
57.90
2016-10-15 22:00:00
56.07
98.05
150.00
81.24
208.41
51.67
32.25
82.48
134.46
100.07
...
164.11
137.85
28.59
127.32
59.24
91.96
88.84
94.80
142.51
21.77
2016-10-16 00:00:00
59.43
60.06
18.62
71.69
38.50
176.72
45.70
300.65
93.32
45.35
...
20.83
53.37
21.36
16.20
27.07
45.09
9.92
22.18
18.98
8.17
2016-10-16 02:00:00
91.74
35.27
15.58
12.09
8.36
17.12
36.26
35.20
10.38
25.51
...
11.06
206.38
13.87
11.76
54.07
126.42
12.01
29.13
12.14
7.78
2016-10-16 04:00:00
45.65
28.72
9.91
23.75
15.55
9.84
42.17
40.29
30.23
35.97
...
22.54
86.44
114.24
26.15
44.47
94.31
36.27
48.22
285.05
33.00
2016-10-16 06:00:00
44.35
107.90
56.34
62.56
74.69
42.83
43.37
97.01
64.27
90.34
...
112.56
94.86
137.52
72.12
49.07
101.45
116.25
105.92
186.40
189.78
2016-10-16 08:00:00
65.10
114.11
112.75
93.91
166.49
64.31
78.61
135.07
102.82
98.29
...
121.36
80.88
177.79
141.18
66.83
227.94
97.21
94.94
165.23
181.15
2016-10-16 10:00:00
72.15
171.94
103.33
54.65
210.89
124.70
70.30
132.77
124.10
79.78
...
149.32
59.31
144.38
103.01
55.31
95.59
80.95
126.53
440.99
227.12
2016-10-16 12:00:00
64.06
93.59
134.29
100.55
266.24
152.97
54.81
95.45
143.35
102.87
...
112.56
99.43
195.02
230.93
79.16
183.45
132.12
111.54
201.60
201.56
2016-10-16 14:00:00
52.68
175.09
149.55
103.92
253.72
190.71
60.43
118.46
91.03
128.19
...
128.09
135.54
234.90
209.33
66.86
85.67
120.06
106.91
210.66
286.61
2016-10-16 16:00:00
72.75
168.21
133.51
103.95
264.98
235.16
71.52
164.68
172.85
97.74
...
153.68
117.52
226.31
215.28
93.63
93.54
183.33
110.75
180.95
224.67
2016-10-16 18:00:00
63.15
135.56
117.24
110.04
241.96
141.09
70.38
128.98
69.72
104.61
...
160.60
68.83
269.18
156.06
68.37
94.52
52.30
104.63
202.09
190.96
2016-10-16 20:00:00
64.10
123.63
120.15
87.52
164.39
153.81
54.89
104.32
112.66
90.29
...
106.95
81.92
224.93
65.92
357.05
105.93
110.85
78.72
74.71
57.90
2016-10-16 22:00:00
64.01
103.64
35.65
106.78
183.47
51.67
58.27
105.03
37.17
62.19
...
80.86
61.42
28.59
34.71
52.26
84.51
23.50
90.29
35.92
21.77
2016-10-17 00:00:00
59.61
89.41
95.71
70.85
38.50
27.91
40.03
77.48
16.13
125.27
...
106.77
88.43
21.36
16.20
27.07
45.09
9.92
22.18
18.98
8.17
2016-10-17 02:00:00
37.09
35.27
15.58
28.74
8.36
17.12
51.25
35.20
10.38
25.51
...
11.06
93.78
13.87
11.76
47.24
46.12
12.01
29.13
12.14
7.78
2016-10-17 04:00:00
56.49
91.66
9.91
73.25
15.55
9.84
69.42
126.47
30.23
35.97
...
22.54
48.19
30.07
26.15
45.24
72.77
135.14
113.93
67.51
33.00
2016-10-17 06:00:00
43.74
68.25
56.34
83.62
196.30
42.83
48.09
140.63
75.72
43.62
...
73.54
69.52
224.46
72.12
72.16
171.10
136.97
110.83
168.88
60.60
2016-10-17 08:00:00
133.58
306.58
108.63
147.11
165.10
64.31
108.33
296.26
115.41
118.52
...
108.23
149.29
151.34
104.67
53.21
128.11
122.42
120.32
265.43
218.18
2016-10-17 10:00:00
64.87
118.49
161.91
129.52
142.21
220.20
76.01
132.14
88.98
50.23
...
102.55
102.44
153.59
93.07
44.09
98.61
100.05
109.67
172.90
88.35
2016-10-17 12:00:00
65.24
99.45
131.03
94.10
167.98
104.38
45.44
104.89
104.69
77.63
...
111.03
84.63
218.76
169.18
64.32
93.51
134.56
81.00
165.84
149.21
2016-10-17 14:00:00
52.28
84.48
99.41
98.19
191.14
131.23
70.19
100.53
147.23
104.86
...
138.69
82.67
134.58
124.07
71.70
131.03
76.92
126.84
483.07
125.78
2016-10-17 16:00:00
53.86
109.92
134.99
115.47
180.28
171.02
69.77
111.73
136.45
100.27
...
130.78
118.25
170.14
122.02
53.69
125.55
177.36
102.55
132.85
107.45
2016-10-17 18:00:00
65.40
158.01
77.42
102.74
267.11
173.74
48.66
115.05
98.47
83.02
...
62.14
91.64
83.93
79.10
65.93
86.11
99.04
96.84
188.23
187.43
2016-10-17 20:00:00
52.66
101.30
62.67
99.77
90.82
209.32
72.69
137.58
172.53
84.75
...
61.55
61.96
121.61
159.44
39.55
100.03
46.81
73.88
74.71
57.90
83 rows × 36 columns
In [12]:
x_test
Out[12]:
hour
minute
weekday
2016-10-11 00:00:00
0
0
1
2016-10-11 02:00:00
2
0
1
2016-10-11 04:00:00
4
0
1
2016-10-11 06:00:00
6
0
1
2016-10-11 08:00:00
8
0
1
2016-10-11 10:00:00
10
0
1
2016-10-11 12:00:00
12
0
1
2016-10-11 14:00:00
14
0
1
2016-10-11 16:00:00
16
0
1
2016-10-11 18:00:00
18
0
1
2016-10-11 20:00:00
20
0
1
2016-10-11 22:00:00
22
0
1
2016-10-12 00:00:00
0
0
2
2016-10-12 02:00:00
2
0
2
2016-10-12 04:00:00
4
0
2
2016-10-12 06:00:00
6
0
2
2016-10-12 08:00:00
8
0
2
2016-10-12 10:00:00
10
0
2
2016-10-12 12:00:00
12
0
2
2016-10-12 14:00:00
14
0
2
2016-10-12 16:00:00
16
0
2
2016-10-12 18:00:00
18
0
2
2016-10-12 20:00:00
20
0
2
2016-10-12 22:00:00
22
0
2
2016-10-13 00:00:00
0
0
3
2016-10-13 02:00:00
2
0
3
2016-10-13 04:00:00
4
0
3
2016-10-13 06:00:00
6
0
3
2016-10-13 08:00:00
8
0
3
2016-10-13 10:00:00
10
0
3
...
...
...
...
2016-10-15 10:00:00
10
0
5
2016-10-15 12:00:00
12
0
5
2016-10-15 14:00:00
14
0
5
2016-10-15 16:00:00
16
0
5
2016-10-15 18:00:00
18
0
5
2016-10-15 20:00:00
20
0
5
2016-10-15 22:00:00
22
0
5
2016-10-16 00:00:00
0
0
6
2016-10-16 02:00:00
2
0
6
2016-10-16 04:00:00
4
0
6
2016-10-16 06:00:00
6
0
6
2016-10-16 08:00:00
8
0
6
2016-10-16 10:00:00
10
0
6
2016-10-16 12:00:00
12
0
6
2016-10-16 14:00:00
14
0
6
2016-10-16 16:00:00
16
0
6
2016-10-16 18:00:00
18
0
6
2016-10-16 20:00:00
20
0
6
2016-10-16 22:00:00
22
0
6
2016-10-17 00:00:00
0
0
0
2016-10-17 02:00:00
2
0
0
2016-10-17 04:00:00
4
0
0
2016-10-17 06:00:00
6
0
0
2016-10-17 08:00:00
8
0
0
2016-10-17 10:00:00
10
0
0
2016-10-17 12:00:00
12
0
0
2016-10-17 14:00:00
14
0
0
2016-10-17 16:00:00
16
0
0
2016-10-17 18:00:00
18
0
0
2016-10-17 20:00:00
20
0
0
83 rows × 3 columns
In [16]:
from sklearn.externals import joblib
from sklearn import svm
from sklearn.multioutput import MultiOutputRegressor
clf = svm.SVR(C=30, epsilon=0.005, cache_size=2000)
regr_multi_svr = MultiOutputRegressor(clf, n_jobs=-1)
regr_multi_svr.fit(x_train, y_train)
# load
regr_multi_svr = joblib.load('regr_multi_svr_timeInformation.pkl')
In [ ]:
from sklearn.externals import joblib
#joblib.dump(regr_multi_svr, 'regr_multi_svr_timeInformation.pkl')
In [17]:
y_test_predict = regr_multi_svr.predict(x_test)
y_test_predict_df = pd.DataFrame(y_test_predict, columns=y_cols)
y_test_predict_df.head()
Out[17]:
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5 rows × 36 columns
In [18]:
regr_multi_svr.score(x_test, y_test)
Out[18]:
0.24468351252499834
In [16]:
from sklearn import metrics
print(metrics.mean_absolute_error(y_test_predict, y_test))
print(metrics.mean_squared_error(y_test_predict, y_test))
import src.misc.evaluation as ev
mymape = ev.mape(y_test_predict, y_test)
print(np.mean(np.array(mymape)))
28.10626237
2815.47733885
0.209518459546
In [21]:
y_test_predict_df
Out[21]:
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64.335179
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110.614652
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118.882101
51.675237
53.804992
83.635983
37.174622
73.365314
...
32.595212
89.672200
28.594671
34.715083
41.334913
72.714854
23.504659
51.564165
35.925155
21.775120
72
46.015113
60.065164
18.625188
76.124626
38.505032
27.914674
47.840922
86.145141
16.135024
45.354981
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20.835015
39.414921
21.365231
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27.075138
45.094928
9.924949
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37.095429
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11.065210
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29.135299
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7.785287
74
51.525115
56.730948
9.915137
34.541980
15.554885
9.845044
50.990002
56.830737
41.318366
35.974936
...
22.545307
67.144830
30.075085
26.155105
63.205232
115.214623
36.274990
67.794843
87.233600
33.004865
75
44.394920
94.284847
82.344714
62.565303
74.695437
42.834630
55.594971
102.494648
64.274584
83.664868
...
95.494670
103.894997
92.154808
76.436185
69.624817
144.174416
86.025044
117.455064
145.799208
60.605094
76
92.823365
146.384773
97.064847
109.754664
157.488364
64.314579
84.154736
125.954923
89.375127
106.855252
...
104.945847
132.592230
149.254877
154.094643
74.712049
130.355339
106.845268
118.984924
132.774966
108.184630
77
76.724647
138.489339
109.235110
121.304800
145.644770
100.984980
68.764906
115.725405
121.705096
118.164630
...
99.831104
110.955385
142.964856
93.074945
59.387698
103.475045
80.955218
103.724942
128.405173
137.045391
78
60.214728
103.295394
90.506080
96.244852
155.714878
96.015422
61.004914
109.635000
106.064677
112.164699
...
89.115208
106.644820
153.954620
123.634960
61.705111
107.044927
91.495201
109.545266
139.444645
140.794600
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55.134878
101.255281
109.356330
100.915506
147.604864
137.164627
66.474923
115.555159
101.205155
95.725061
...
100.059361
107.584778
145.364910
171.154907
64.755409
106.171717
76.218193
110.664661
137.865085
125.785347
80
65.474796
102.924898
89.674694
106.855186
154.495339
146.464684
60.814823
105.444977
80.495167
103.225000
...
66.654759
100.495331
128.894661
103.154815
62.214965
118.194789
82.134654
106.505071
135.485175
107.454883
81
61.955219
110.884853
77.424737
107.495292
117.724926
143.267696
68.984999
109.865925
69.725257
107.094692
...
78.105965
86.275298
83.934611
79.105254
63.534928
118.534889
52.304910
104.665270
83.935387
90.564895
82
62.315414
106.174799
62.675070
94.534711
90.825337
72.645120
57.474683
106.685298
59.014808
84.754844
...
61.554743
90.110303
115.895968
65.924942
53.055015
108.165369
46.814974
81.245272
74.714989
57.905387
83 rows × 36 columns
In [40]:
y_test
Out[40]:
(0, A2)
(0, A3)
(0, B1)
(0, B3)
(0, C1)
(0, C3)
(1, A2)
(1, A3)
(1, B1)
(1, B3)
...
(4, B1)
(4, B3)
(4, C1)
(4, C3)
(5, A2)
(5, A3)
(5, B1)
(5, B3)
(5, C1)
(5, C3)
2016-10-11 00:00:00
52.28
60.06
18.62
50.16
38.50
27.91
37.07
107.80
16.13
103.27
...
20.83
39.41
21.36
16.20
27.07
45.09
69.89
94.61
18.98
8.17
2016-10-11 02:00:00
37.09
35.27
15.58
28.74
8.36
17.12
52.36
35.20
10.38
75.56
...
11.06
31.36
13.87
11.76
53.40
46.12
99.88
29.13
12.14
7.78
2016-10-11 04:00:00
38.38
45.88
9.91
23.75
15.55
9.84
53.69
40.29
30.23
35.97
...
22.54
48.19
164.07
156.45
41.32
77.45
90.51
48.22
206.02
33.00
2016-10-11 06:00:00
44.41
97.47
125.78
62.56
74.69
42.83
32.56
127.90
96.05
71.58
...
127.86
143.01
158.56
72.12
50.97
137.73
134.92
110.76
173.09
190.27
2016-10-11 08:00:00
68.09
146.16
86.56
142.52
158.31
64.31
75.02
168.43
127.10
93.00
...
120.29
104.09
129.01
202.18
70.26
121.44
93.94
133.37
166.25
117.08
2016-10-11 10:00:00
58.42
134.14
128.12
133.50
241.20
100.98
59.50
122.61
96.85
231.31
...
97.47
93.11
202.58
93.07
72.78
96.14
102.81
102.93
145.38
132.98
2016-10-11 12:00:00
62.17
168.92
140.94
81.62
159.03
206.08
67.42
105.85
134.51
129.76
...
101.64
106.02
188.35
123.63
61.31
122.76
106.54
103.98
198.28
132.72
2016-10-11 14:00:00
63.76
84.14
131.75
160.78
198.61
159.13
70.16
104.73
106.43
110.78
...
120.09
113.49
177.20
124.07
80.86
112.35
107.40
124.56
186.99
151.44
2016-10-11 16:00:00
66.96
102.97
85.30
97.92
151.63
143.58
85.57
100.22
93.09
130.13
...
111.53
103.08
193.29
183.23
67.00
146.57
254.55
76.11
230.08
218.23
2016-10-11 18:00:00
48.92
112.86
204.27
113.66
250.10
95.01
121.45
280.83
126.37
64.97
...
128.57
129.44
160.61
79.10
77.23
115.81
128.59
102.91
170.00
207.18
2016-10-11 20:00:00
88.02
98.23
108.57
95.91
153.19
72.64
53.83
104.47
93.71
84.75
...
61.55
268.29
161.02
122.44
74.66
91.72
350.79
120.55
201.53
218.45
2016-10-11 22:00:00
54.76
95.40
148.41
86.69
162.99
51.67
48.85
97.33
37.17
86.00
...
32.59
136.46
137.63
34.71
50.05
62.06
23.50
39.47
35.92
111.98
2016-10-12 00:00:00
53.89
55.96
18.62
83.32
38.50
27.91
69.38
64.30
16.13
45.35
...
20.83
39.41
21.36
16.20
27.07
67.30
9.92
22.18
18.98
8.17
2016-10-12 02:00:00
35.75
35.27
15.58
28.74
8.36
17.12
57.34
89.27
10.38
105.41
...
11.06
83.37
13.87
11.76
60.73
46.12
12.01
29.13
12.14
7.78
2016-10-12 04:00:00
41.58
82.20
9.91
23.75
15.55
9.84
42.86
40.29
30.23
35.97
...
97.33
87.31
188.20
26.15
58.03
99.03
36.27
48.22
67.51
33.00
2016-10-12 06:00:00
49.68
93.64
100.25
84.28
74.69
42.83
45.53
135.08
64.27
98.94
...
73.54
73.71
92.15
110.15
63.15
138.92
69.42
153.30
143.44
60.60
2016-10-12 08:00:00
86.16
171.63
117.33
84.05
146.38
175.34
83.28
189.11
184.11
156.47
...
132.43
168.48
116.31
104.67
65.32
143.11
87.74
156.67
194.99
215.89
2016-10-12 10:00:00
94.91
131.99
107.56
104.83
121.63
209.00
58.60
99.85
106.44
117.59
...
64.19
76.81
242.19
140.85
57.23
111.28
104.02
110.46
176.85
88.35
2016-10-12 12:00:00
55.71
81.89
120.83
92.75
180.54
174.42
61.98
100.87
82.99
26.74
...
132.50
103.32
142.53
176.53
64.27
112.77
85.15
103.29
139.48
160.53
2016-10-12 14:00:00
71.25
105.32
113.41
92.04
172.53
115.48
62.77
109.13
142.55
87.21
...
96.16
81.32
221.58
218.83
50.12
99.73
143.76
95.90
151.01
141.39
2016-10-12 16:00:00
60.51
97.40
126.86
86.15
153.51
170.92
57.58
83.99
111.50
111.87
...
66.65
93.10
172.73
148.58
78.55
114.99
110.97
103.29
171.72
196.05
2016-10-12 18:00:00
81.69
113.32
127.47
160.28
186.11
146.06
52.32
112.96
132.60
87.50
...
62.14
102.74
169.59
203.03
67.94
101.71
52.30
51.49
196.28
90.56
2016-10-12 20:00:00
76.01
100.00
89.78
82.10
183.10
72.64
57.85
110.36
130.23
113.44
...
96.42
97.17
162.05
65.92
66.46
89.55
46.81
98.05
74.71
57.90
2016-10-12 22:00:00
58.35
112.08
35.65
68.51
156.96
51.67
35.44
46.24
96.12
71.62
...
99.06
80.30
112.53
34.71
42.57
56.12
23.50
121.04
35.92
21.77
2016-10-13 00:00:00
74.92
60.06
18.62
50.16
38.50
27.91
46.58
91.02
16.13
45.35
...
20.83
39.41
21.36
16.20
50.53
45.09
94.23
22.18
18.98
97.82
2016-10-13 02:00:00
129.60
93.48
15.58
28.74
145.63
17.12
52.09
95.52
10.38
25.51
...
68.08
31.36
13.87
11.76
73.72
46.12
12.01
29.13
12.14
7.78
2016-10-13 04:00:00
54.43
73.95
9.91
23.75
142.71
9.84
57.76
106.28
100.69
35.97
...
22.54
107.66
30.07
26.15
37.66
87.00
36.27
95.92
67.51
33.00
2016-10-13 06:00:00
54.31
121.44
119.71
62.56
127.55
42.83
77.89
92.64
138.09
83.66
...
140.66
16.85
92.15
119.28
87.81
114.64
102.54
106.15
214.35
212.35
2016-10-13 08:00:00
82.59
176.52
117.33
113.20
169.92
194.72
85.20
105.61
119.43
82.62
...
109.39
67.84
176.34
104.67
67.78
96.76
146.40
107.55
152.02
187.55
2016-10-13 10:00:00
65.09
105.11
137.43
82.42
182.90
159.94
61.71
119.30
121.10
117.33
...
178.25
110.95
149.97
93.07
53.17
144.99
107.04
104.34
134.46
137.87
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
2016-10-15 10:00:00
141.55
479.41
193.03
82.13
130.52
195.73
142.34
225.43
215.81
80.56
...
102.47
99.52
183.99
243.18
51.78
110.14
126.93
125.04
193.78
178.96
2016-10-15 12:00:00
55.49
108.68
148.88
90.00
175.20
91.15
75.10
102.03
194.71
111.61
...
131.88
123.81
311.30
211.62
76.85
107.19
322.43
94.48
345.66
210.76
2016-10-15 14:00:00
70.85
101.44
369.30
147.15
480.54
131.23
68.73
129.67
132.41
112.88
...
99.66
72.51
226.76
200.01
64.57
105.97
166.30
131.37
220.01
195.49
2016-10-15 16:00:00
62.82
186.11
131.17
120.68
183.74
173.84
55.51
136.59
187.96
156.38
...
118.43
143.56
288.68
201.31
56.20
131.52
208.65
116.47
156.18
176.67
2016-10-15 18:00:00
69.84
140.16
117.03
92.53
208.13
95.01
61.47
107.73
113.36
39.24
...
62.14
104.38
174.08
79.10
54.73
116.60
121.98
76.71
83.93
187.67
2016-10-15 20:00:00
49.56
113.54
131.56
81.32
90.82
557.39
71.34
85.96
92.39
73.55
...
61.55
75.68
160.54
127.78
61.11
85.04
152.00
81.70
181.06
57.90
2016-10-15 22:00:00
56.07
98.05
150.00
81.24
208.41
51.67
32.25
82.48
134.46
100.07
...
164.11
137.85
28.59
127.32
59.24
91.96
88.84
94.80
142.51
21.77
2016-10-16 00:00:00
59.43
60.06
18.62
71.69
38.50
176.72
45.70
300.65
93.32
45.35
...
20.83
53.37
21.36
16.20
27.07
45.09
9.92
22.18
18.98
8.17
2016-10-16 02:00:00
91.74
35.27
15.58
12.09
8.36
17.12
36.26
35.20
10.38
25.51
...
11.06
206.38
13.87
11.76
54.07
126.42
12.01
29.13
12.14
7.78
2016-10-16 04:00:00
45.65
28.72
9.91
23.75
15.55
9.84
42.17
40.29
30.23
35.97
...
22.54
86.44
114.24
26.15
44.47
94.31
36.27
48.22
285.05
33.00
2016-10-16 06:00:00
44.35
107.90
56.34
62.56
74.69
42.83
43.37
97.01
64.27
90.34
...
112.56
94.86
137.52
72.12
49.07
101.45
116.25
105.92
186.40
189.78
2016-10-16 08:00:00
65.10
114.11
112.75
93.91
166.49
64.31
78.61
135.07
102.82
98.29
...
121.36
80.88
177.79
141.18
66.83
227.94
97.21
94.94
165.23
181.15
2016-10-16 10:00:00
72.15
171.94
103.33
54.65
210.89
124.70
70.30
132.77
124.10
79.78
...
149.32
59.31
144.38
103.01
55.31
95.59
80.95
126.53
440.99
227.12
2016-10-16 12:00:00
64.06
93.59
134.29
100.55
266.24
152.97
54.81
95.45
143.35
102.87
...
112.56
99.43
195.02
230.93
79.16
183.45
132.12
111.54
201.60
201.56
2016-10-16 14:00:00
52.68
175.09
149.55
103.92
253.72
190.71
60.43
118.46
91.03
128.19
...
128.09
135.54
234.90
209.33
66.86
85.67
120.06
106.91
210.66
286.61
2016-10-16 16:00:00
72.75
168.21
133.51
103.95
264.98
235.16
71.52
164.68
172.85
97.74
...
153.68
117.52
226.31
215.28
93.63
93.54
183.33
110.75
180.95
224.67
2016-10-16 18:00:00
63.15
135.56
117.24
110.04
241.96
141.09
70.38
128.98
69.72
104.61
...
160.60
68.83
269.18
156.06
68.37
94.52
52.30
104.63
202.09
190.96
2016-10-16 20:00:00
64.10
123.63
120.15
87.52
164.39
153.81
54.89
104.32
112.66
90.29
...
106.95
81.92
224.93
65.92
357.05
105.93
110.85
78.72
74.71
57.90
2016-10-16 22:00:00
64.01
103.64
35.65
106.78
183.47
51.67
58.27
105.03
37.17
62.19
...
80.86
61.42
28.59
34.71
52.26
84.51
23.50
90.29
35.92
21.77
2016-10-17 00:00:00
59.61
89.41
95.71
70.85
38.50
27.91
40.03
77.48
16.13
125.27
...
106.77
88.43
21.36
16.20
27.07
45.09
9.92
22.18
18.98
8.17
2016-10-17 02:00:00
37.09
35.27
15.58
28.74
8.36
17.12
51.25
35.20
10.38
25.51
...
11.06
93.78
13.87
11.76
47.24
46.12
12.01
29.13
12.14
7.78
2016-10-17 04:00:00
56.49
91.66
9.91
73.25
15.55
9.84
69.42
126.47
30.23
35.97
...
22.54
48.19
30.07
26.15
45.24
72.77
135.14
113.93
67.51
33.00
2016-10-17 06:00:00
43.74
68.25
56.34
83.62
196.30
42.83
48.09
140.63
75.72
43.62
...
73.54
69.52
224.46
72.12
72.16
171.10
136.97
110.83
168.88
60.60
2016-10-17 08:00:00
133.58
306.58
108.63
147.11
165.10
64.31
108.33
296.26
115.41
118.52
...
108.23
149.29
151.34
104.67
53.21
128.11
122.42
120.32
265.43
218.18
2016-10-17 10:00:00
64.87
118.49
161.91
129.52
142.21
220.20
76.01
132.14
88.98
50.23
...
102.55
102.44
153.59
93.07
44.09
98.61
100.05
109.67
172.90
88.35
2016-10-17 12:00:00
65.24
99.45
131.03
94.10
167.98
104.38
45.44
104.89
104.69
77.63
...
111.03
84.63
218.76
169.18
64.32
93.51
134.56
81.00
165.84
149.21
2016-10-17 14:00:00
52.28
84.48
99.41
98.19
191.14
131.23
70.19
100.53
147.23
104.86
...
138.69
82.67
134.58
124.07
71.70
131.03
76.92
126.84
483.07
125.78
2016-10-17 16:00:00
53.86
109.92
134.99
115.47
180.28
171.02
69.77
111.73
136.45
100.27
...
130.78
118.25
170.14
122.02
53.69
125.55
177.36
102.55
132.85
107.45
2016-10-17 18:00:00
65.40
158.01
77.42
102.74
267.11
173.74
48.66
115.05
98.47
83.02
...
62.14
91.64
83.93
79.10
65.93
86.11
99.04
96.84
188.23
187.43
2016-10-17 20:00:00
52.66
101.30
62.67
99.77
90.82
209.32
72.69
137.58
172.53
84.75
...
61.55
61.96
121.61
159.44
39.55
100.03
46.81
73.88
74.71
57.90
83 rows × 36 columns
In [46]:
#plot
import matplotlib.pyplot as plt
alpha=0.8
lw=0.7
fig, ax = plt.subplots(figsize = (26,8))
x_a = [pd.to_datetime(d) for d in y_test.index.values]
ax.scatter(np.array(x_a), y_test['0','A2'], color='green', label='y_test', s=0.8)
#ax.plot(x_a, y_test_predict_df['0','A2'], color='red', label='y_pred_rbf', alpha=alpha, lw=lw)
#plt.plot(x_a, y_test_predict_df['1','A2'], color='blue', label='y_pred_sigmoid', alpha=alpha, lw=lw)
#ax.plot(res.index.values, res['y_pred_lin'], color='orange', label='y_pred_lin', alpha=alpha, lw=lw)
#plt.plot(res.index.values, res['y_pred'], color='darkorange', label='y_pred_rbf')
ax.set_title('SVN on TimeInformation with rbf and linear kernel')
ax.set_xlabel('index(route,dayofweek,hour,minute)')
ax.set_ylabel('avg_travel_time')
ax.set_ylim(0,200)
ax.set_xlim(0)
ax.legend(shadow=True, fancybox=True)
#fig.legend()
'''
I also want to share my recent results. Maybe it helps or inspire someone.
SVN on TimeInformation with rbf and linear kernel.
Trained on the first 8 weeks and tested with the remaining data. (not shuffled)
'''
Out[46]:
'\nI also want to share my recent results. Maybe it helps or inspire someone.\n\nSVN on TimeInformation with rbf and linear kernel.\nTrained on the first 8 weeks and tested with the remaining data. (not shuffled)\n\n'
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
C:\Anaconda3\lib\site-packages\IPython\core\formatters.py in __call__(self, obj)
305 pass
306 else:
--> 307 return printer(obj)
308 # Finally look for special method names
309 method = get_real_method(obj, self.print_method)
C:\Anaconda3\lib\site-packages\IPython\core\pylabtools.py in <lambda>(fig)
225
226 if 'png' in formats:
--> 227 png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
228 if 'retina' in formats or 'png2x' in formats:
229 png_formatter.for_type(Figure, lambda fig: retina_figure(fig, **kwargs))
C:\Anaconda3\lib\site-packages\IPython\core\pylabtools.py in print_figure(fig, fmt, bbox_inches, **kwargs)
117
118 bytes_io = BytesIO()
--> 119 fig.canvas.print_figure(bytes_io, **kw)
120 data = bytes_io.getvalue()
121 if fmt == 'svg':
C:\Anaconda3\lib\site-packages\matplotlib\backend_bases.py in print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, **kwargs)
2178 orientation=orientation,
2179 dryrun=True,
-> 2180 **kwargs)
2181 renderer = self.figure._cachedRenderer
2182 bbox_inches = self.figure.get_tightbbox(renderer)
C:\Anaconda3\lib\site-packages\matplotlib\backends\backend_agg.py in print_png(self, filename_or_obj, *args, **kwargs)
525
526 def print_png(self, filename_or_obj, *args, **kwargs):
--> 527 FigureCanvasAgg.draw(self)
528 renderer = self.get_renderer()
529 original_dpi = renderer.dpi
C:\Anaconda3\lib\site-packages\matplotlib\backends\backend_agg.py in draw(self)
472
473 try:
--> 474 self.figure.draw(self.renderer)
475 finally:
476 RendererAgg.lock.release()
C:\Anaconda3\lib\site-packages\matplotlib\artist.py in draw_wrapper(artist, renderer, *args, **kwargs)
60 def draw_wrapper(artist, renderer, *args, **kwargs):
61 before(artist, renderer)
---> 62 draw(artist, renderer, *args, **kwargs)
63 after(artist, renderer)
64
C:\Anaconda3\lib\site-packages\matplotlib\figure.py in draw(self, renderer)
1157 dsu.sort(key=itemgetter(0))
1158 for zorder, a, func, args in dsu:
-> 1159 func(*args)
1160
1161 renderer.close_group('figure')
C:\Anaconda3\lib\site-packages\matplotlib\artist.py in draw_wrapper(artist, renderer, *args, **kwargs)
60 def draw_wrapper(artist, renderer, *args, **kwargs):
61 before(artist, renderer)
---> 62 draw(artist, renderer, *args, **kwargs)
63 after(artist, renderer)
64
C:\Anaconda3\lib\site-packages\matplotlib\axes\_base.py in draw(self, renderer, inframe)
2317
2318 for zorder, a in dsu:
-> 2319 a.draw(renderer)
2320
2321 renderer.close_group('axes')
C:\Anaconda3\lib\site-packages\matplotlib\artist.py in draw_wrapper(artist, renderer, *args, **kwargs)
60 def draw_wrapper(artist, renderer, *args, **kwargs):
61 before(artist, renderer)
---> 62 draw(artist, renderer, *args, **kwargs)
63 after(artist, renderer)
64
C:\Anaconda3\lib\site-packages\matplotlib\axis.py in draw(self, renderer, *args, **kwargs)
1106 renderer.open_group(__name__)
1107
-> 1108 ticks_to_draw = self._update_ticks(renderer)
1109 ticklabelBoxes, ticklabelBoxes2 = self._get_tick_bboxes(ticks_to_draw,
1110 renderer)
C:\Anaconda3\lib\site-packages\matplotlib\axis.py in _update_ticks(self, renderer)
949
950 interval = self.get_view_interval()
--> 951 tick_tups = [t for t in self.iter_ticks()]
952 if self._smart_bounds:
953 # handle inverted limits
C:\Anaconda3\lib\site-packages\matplotlib\axis.py in <listcomp>(.0)
949
950 interval = self.get_view_interval()
--> 951 tick_tups = [t for t in self.iter_ticks()]
952 if self._smart_bounds:
953 # handle inverted limits
C:\Anaconda3\lib\site-packages\matplotlib\axis.py in iter_ticks(self)
892 Iterate through all of the major and minor ticks.
893 """
--> 894 majorLocs = self.major.locator()
895 majorTicks = self.get_major_ticks(len(majorLocs))
896 self.major.formatter.set_locs(majorLocs)
C:\Anaconda3\lib\site-packages\matplotlib\dates.py in __call__(self)
1005 def __call__(self):
1006 'Return the locations of the ticks'
-> 1007 self.refresh()
1008 return self._locator()
1009
C:\Anaconda3\lib\site-packages\matplotlib\dates.py in refresh(self)
1025 def refresh(self):
1026 'Refresh internal information based on current limits.'
-> 1027 dmin, dmax = self.viewlim_to_dt()
1028 self._locator = self.get_locator(dmin, dmax)
1029
C:\Anaconda3\lib\site-packages\matplotlib\dates.py in viewlim_to_dt(self)
769 vmin, vmax = vmax, vmin
770
--> 771 return num2date(vmin, self.tz), num2date(vmax, self.tz)
772
773 def _get_unit(self):
C:\Anaconda3\lib\site-packages\matplotlib\dates.py in num2date(x, tz)
417 tz = _get_rc_timezone()
418 if not cbook.iterable(x):
--> 419 return _from_ordinalf(x, tz)
420 else:
421 x = np.asarray(x)
C:\Anaconda3\lib\site-packages\matplotlib\dates.py in _from_ordinalf(x, tz)
269
270 ix = int(x)
--> 271 dt = datetime.datetime.fromordinal(ix).replace(tzinfo=UTC)
272
273 remainder = float(x) - ix
ValueError: ordinal must be >= 1
<matplotlib.figure.Figure at 0x2d28f1806a0>
In [17]:
from sklearn.multioutput import MultiOutputRegressor
from sklearn.svm import SVR
from sklearn.model_selection import GridSearchCV
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
pipe_svr = Pipeline([ ('reg', MultiOutputRegressor(SVR()))])
grid_param_svr = {
'reg__estimator__C': np.arange(20, 40.0, 2.0),
"reg__estimator__epsilon": [0.0, 0.0001, 0.001, 0.0025, 0.005]
}
gs_svr = (GridSearchCV(estimator=pipe_svr,
param_grid=grid_param_svr,
cv=2,
scoring = 'neg_mean_squared_error',
n_jobs = -1))
gs_svr = gs_svr.fit(x_train,y_train)
In [18]:
print(gs_svr.best_estimator_)
print(gs_svr.best_params_)
pd.DataFrame(gs_svr.cv_results_).sort_values('rank_test_score')
Pipeline(steps=[('reg', MultiOutputRegressor(estimator=SVR(C=30.0, cache_size=200, coef0=0.0, degree=3, epsilon=0.005, gamma='auto',
kernel='rbf', max_iter=-1, shrinking=True, tol=0.001, verbose=False),
n_jobs=1))])
{'reg__estimator__C': 30.0, 'reg__estimator__epsilon': 0.005}
Out[18]:
mean_fit_time
mean_score_time
mean_test_score
mean_train_score
param_reg__estimator__C
param_reg__estimator__epsilon
params
rank_test_score
split0_test_score
split0_train_score
split1_test_score
split1_train_score
std_fit_time
std_score_time
std_test_score
std_train_score
29
1.485690
0.272784
-2922.220954
-2480.605715
30
0.005
{'reg__estimator__C': 30.0, 'reg__estimator__e...
1
-2527.670003
-2652.004460
-3316.771905
-2309.206970
0.099013
0.041755
394.550951
171.398745
34
1.551198
0.237281
-2922.250148
-2477.496665
32
0.005
{'reg__estimator__C': 32.0, 'reg__estimator__e...
2
-2529.336965
-2650.288076
-3315.163331
-2304.705255
0.112514
0.009751
392.913183
172.791411
28
1.529694
0.239030
-2922.260523
-2480.642198
30
0.0025
{'reg__estimator__C': 30.0, 'reg__estimator__e...
3
-2527.693491
-2652.033039
-3316.827555
-2309.251356
0.142018
0.000500
394.567032
171.390842
27
1.503191
0.232280
-2922.283798
-2480.663840
30
0.001
{'reg__estimator__C': 30.0, 'reg__estimator__e...
4
-2527.707637
-2652.050136
-3316.859959
-2309.277545
0.127516
0.010751
394.576161
171.386296
33
1.550447
0.239530
-2922.290200
-2477.533470
32
0.0025
{'reg__estimator__C': 32.0, 'reg__estimator__e...
5
-2529.361020
-2650.317342
-3315.219381
-2304.749598
0.114764
0.004500
392.929181
172.783872
26
1.492940
0.230529
-2922.297897
-2480.677186
30
0.0001
{'reg__estimator__C': 30.0, 'reg__estimator__e...
6
-2527.715912
-2652.060650
-3316.879882
-2309.293721
0.114264
0.008001
394.581985
171.383464
25
1.485939
0.236280
-2922.299018
-2480.678231
30
0
{'reg__estimator__C': 30.0, 'reg__estimator__e...
7
-2527.717053
-2652.061656
-3316.880983
-2309.294806
0.111264
0.002250
394.581965
171.383425
32
1.543446
0.234030
-2922.314287
-2477.555871
32
0.001
{'reg__estimator__C': 32.0, 'reg__estimator__e...
8
-2529.375446
-2650.335371
-3315.253128
-2304.776371
0.135767
0.003501
392.938841
172.779500
31
1.527663
0.235530
-2922.328628
-2477.569152
32
0.0001
{'reg__estimator__C': 32.0, 'reg__estimator__e...
9
-2529.383768
-2650.345625
-3315.273489
-2304.792680
0.113545
0.004500
392.944861
172.776472
30
1.517932
0.233279
-2922.329924
-2477.570385
32
0
{'reg__estimator__C': 32.0, 'reg__estimator__e...
10
-2529.384688
-2650.346807
-3315.275159
-2304.793964
0.109775
0.009751
392.945235
172.776422
39
1.538695
0.241531
-2922.428757
-2474.470755
34
0.005
{'reg__estimator__C': 34.0, 'reg__estimator__e...
11
-2531.156279
-2648.703374
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0.082010
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38
1.647959
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34
0.0025
{'reg__estimator__C': 34.0, 'reg__estimator__e...
12
-2531.179223
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24
1.436183
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28
0.005
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-2526.396716
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37
1.840234
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34
0.001
{'reg__estimator__C': 34.0, 'reg__estimator__e...
14
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0.050006
0.020503
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36
1.901242
0.319290
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34
0.0001
{'reg__estimator__C': 34.0, 'reg__estimator__e...
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34
0
{'reg__estimator__C': 34.0, 'reg__estimator__e...
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23
1.445184
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28
0.0025
{'reg__estimator__C': 28.0, 'reg__estimator__e...
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-2526.419464
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0.0025
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8
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0.0025
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24
0.005
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7
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22
0.001
{'reg__estimator__C': 22.0, 'reg__estimator__e...
29
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6
1.445934
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22
0.0001
{'reg__estimator__C': 22.0, 'reg__estimator__e...
30
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0.128267
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5
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22
0
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31
-2520.995615
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19
1.434932
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26
0.005
{'reg__estimator__C': 26.0, 'reg__estimator__e...
32
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0.110264
0.003251
397.575069
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13
1.413430
0.235780
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24
0.0025
{'reg__estimator__C': 24.0, 'reg__estimator__e...
33
-2523.225694
-2657.815670
-3322.420956
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0.109764
0.015252
399.597631
166.781405
12
1.437933
0.233280
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-2491.053893
24
0.001
{'reg__estimator__C': 24.0, 'reg__estimator__e...
34
-2523.239482
-2657.829934
-3322.452360
-2324.277852
0.120765
0.005750
399.606439
166.776041
18
1.419180
0.234530
-2922.857742
-2487.242072
26
0.0025
{'reg__estimator__C': 26.0, 'reg__estimator__e...
35
-2525.268214
-2655.681745
-3320.447269
-2318.802398
0.097512
0.009501
397.589527
168.439673
11
1.543447
0.234030
-2922.859941
-2491.066405
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Content source: Superchicken1/SambaFlow
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