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Merge old branches to refactor due to merge it with master #22

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s481825 merged 20 commits from tree into refactor 2024-06-04 11:36:14 +02:00
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Data/dataTree2.csv Normal file
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plant_water_level,growth,disease,fertility,tractor_water_level,temperature,rain,season,current_time,action
1,20,0,40,60,2,0,2,1,1
20,40,0,40,60,2,0,2,1,1
87,20,0,40,60,2,0,2,1,0
27,43,1,40,60,2,0,2,1,0
89,56,1,40,60,2,1,1,1,0
67,100,1,37,55,1,3,3,3,0
67,40,1,87,90,4,0,1,0,0
1,20,0,40,60,2,0,0,1,0
20,40,0,40,60,2,0,0,1,0
87,20,0,56,45,2,0,0,2,0
27,43,1,40,60,2,0,0,3,0
89,56,1,40,89,2,1,0,1,0
67,100,1,37,55,1,3,0,3,0
67,40,1,87,90,4,0,0,0,0
1,100,0,45,20,2,0,2,1,0
20,100,0,40,34,0,1,2,0,0
87,100,0,56,60,2,0,1,1,0
27,100,0,89,67,1,2,2,2,0
89,100,0,40,60,2,1,1,1,0
76,100,0,37,55,1,3,3,3,0
67,100,0,87,90,4,0,1,0,0
1,20,0,40,0,2,0,2,1,0
20,40,0,40,0,2,0,2,1,0
87,20,0,40,0,2,0,2,1,0
27,43,1,40,0,2,0,2,1,0
89,56,1,40,0,2,1,1,1,0
67,100,1,37,0,1,3,3,3,0
67,40,1,87,0,4,0,1,0,0
1,20,0,40,0,2,0,0,1,0
20,40,0,40,0,2,0,0,1,0
87,20,0,56,0,2,0,0,2,0
27,43,1,40,0,2,0,0,3,0
89,56,1,40,0,2,1,0,1,0
67,100,1,37,0,1,3,0,3,0
67,40,1,87,0,4,0,0,0,0
1,100,0,45,0,2,0,2,1,0
20,100,0,40,0,0,1,2,0,0
87,100,0,56,0,2,0,1,1,0
27,100,0,89,0,1,2,2,2,0
89,100,0,40,0,2,1,1,1,0
76,100,0,37,0,1,3,3,3,0
67,100,0,87,0,4,0,1,0,0
1,45,0,56,44,2,1,1,1,1
20,55,0,43,34,2,0,2,2,1
15,23,0,23,26,2,1,3,3,1
45,67,0,12,67,3,0,1,0,1
59,88,0,34,87,3,0,2,1,1
32,32,0,32,90,3,0,3,2,1
44,43,0,19,27,2,0,1,3,1
33,11,0,28,76,2,0,2,0,1
54,90,0,44,5,3,0,3,1,1
21,76,0,50,25,3,1,1,2,1
29,64,0,38,36,2,0,2,3,1
11,54,0,65,44,3,1,1,2,1
23,55,0,34,43,3,0,2,1,1
51,32,0,32,62,3,1,3,3,1
54,76,0,21,76,2,0,1,2,1
95,88,0,43,78,2,0,2,1,0
23,23,0,23,9,2,0,3,3,1
44,34,0,91,72,3,0,1,0,1
33,11,0,82,67,3,0,2,2,1
45,9,0,44,50,2,0,3,3,1
21,67,0,50,52,2,1,1,0,1
92,46,0,83,63,3,0,2,1,0
20,55,1,43,34,0,0,2,2,0
15,23,1,23,26,0,1,3,3,0
45,67,1,12,67,0,0,1,0,0
59,88,1,34,87,0,0,2,1,0
32,32,0,32,90,0,0,3,2,0
44,43,0,19,27,4,0,1,3,0
33,11,0,28,76,4,0,2,0,0
54,90,0,44,5,4,0,3,1,0
21,76,0,50,25,4,1,1,2,0
29,64,0,38,36,4,0,2,3,0
11,54,0,65,44,0,1,1,2,0
23,55,0,34,43,0,0,2,1,0
51,32,0,32,62,0,1,3,3,0
80,76,1,39,7,3,0,1,0,0
98,77,0,15,91,1,3,2,3,0
3,48,1,73,41,2,2,0,3,0
20,15,1,97,87,4,1,2,1,0
93,6,0,37,0,0,1,0,1,0
4,31,0,1,5,2,3,1,2,0
42,52,0,33,19,3,2,3,0,0
76,43,0,77,18,4,0,0,3,0
31,13,1,21,42,0,1,2,3,0
96,65,1,63,35,1,3,3,2,0
29,39,0,40,37,3,3,0,0,0
82,53,0,55,9,0,1,3,2,0
21,35,0,58,1,1,2,2,0,0
92,98,0,69,16,3,0,0,1,0
34,23,0,95,2,2,3,0,3,0
36,28,0,62,22,0,1,1,1,0
66,88,1,10,85,3,1,2,3,0
53,51,0,79,90,2,2,3,2,0
9,74,0,60,4,4,1,2,3,1
17,0,0,38,58,1,2,3,0,0
12,76,0,50,25,3,1,1,2,1
92,64,0,38,36,2,0,2,3,0
11,54,0,65,44,3,1,1,2,1
32,55,0,34,43,3,0,2,1,1
15,32,0,32,62,3,1,3,3,1
45,76,0,21,76,2,0,1,2,1
59,88,0,43,78,2,0,2,1,1
32,23,0,23,9,2,0,3,3,1
14,34,0,91,72,3,0,1,0,1
13,11,0,82,67,3,0,2,2,1
45,9,0,44,50,2,0,3,3,1
21,67,0,50,52,2,1,1,0,1
92,46,0,83,63,3,0,2,1,0
2,40,1,34,43,1,3,2,2,0
51,32,1,32,62,2,1,3,3,0
54,76,1,21,76,3,0,1,0,0
98,38,0,50,44,4,0,1,0,0
63,7,0,93,79,2,0,2,1,1
91,59,0,94,24,4,0,3,2,0
11,49,0,54,76,2,0,1,3,1
33,31,0,59,39,3,0,1,3,1
28,50,0,26,0,4,0,2,2,0
54,83,0,36,0,3,0,2,1,0
49,78,0,68,0,2,0,3,2,0
59,21,0,43,100,1,0,3,2,1
1,30,0,52,100,2,0,0,3,0
60,9,0,40,40,3,0,0,3,0
85,94,0,87,85,4,0,1,3,0
79,68,0,56,90,1,0,2,2,1
75,22,0,25,95,1,0,3,2,1
100,51,0,33,12,0,0,2,2,0
90,70,0,71,81,0,0,2,1,0
47,26,0,6,78,4,0,1,1,1
14,89,0,70,18,4,0,1,0,1
99,19,0,74,91,2,0,3,0,0
18,48,0,15,32,2,0,3,0,1
5,57,0,14,34,0,1,1,3,1
22,67,0,9,5,0,1,2,2,0
95,81,0,46,86,1,1,3,1,0
39,65,0,84,0,1,1,0,0,0
84,75,0,30,0,2,1,1,1,0
86,41,0,2,67,2,1,2,2,0
64,53,0,53,47,1,1,3,3,1
69,61,0,0,73,2,1,0,0,0
94,40,1,0,18,3,1,1,2,0
62,82,1,20,50,4,1,2,3,0
57,1,1,17,92,0,1,3,2,0
80,35,1,58,45,0,0,3,1,0
30,47,1,8,47,1,0,2,1,0
82,32,0,99,39,1,3,1,3,0
20,84,0,0,51,2,3,2,3,0
42,88,0,0,54,2,2,2,0,0
66,45,0,91,10,3,2,1,0,0
81,14,0,19,55,3,0,1,2,1
74,37,0,88,78,4,0,3,2,1
89,99,0,100,60,4,0,3,3,0
15,20,0,45,11,0,0,1,3,1
92,28,0,85,90,2,0,1,1,0
55,4,0,13,95,2,0,2,1,1
2,6,0,35,0,2,0,2,0,0
61,56,0,90,0,2,0,3,0,0
76,11,0,61,10,3,0,3,1,1
26,80,0,57,9,3,0,1,2,1
40,44,0,81,8,3,0,2,3,1
50,66,0,23,7,3,0,3,0,1
48,15,0,77,6,2,0,0,1,0
11,54,0,65,44,3,3,1,2,0
23,55,0,34,43,3,3,2,1,0
51,32,0,32,62,3,3,3,3,0
54,76,0,21,76,2,3,1,2,0
95,88,0,43,78,2,3,2,1,0
23,23,0,23,9,2,3,3,3,0
44,34,0,91,72,3,3,1,0,0
33,11,0,82,67,3,3,2,2,0
45,9,0,44,50,2,3,3,3,0
21,67,0,50,52,2,3,1,0,0
92,46,0,83,63,3,3,2,1,0
20,55,1,43,34,0,3,2,2,0
15,23,1,23,26,0,3,3,3,0
45,67,1,12,67,0,3,1,0,0
59,88,1,34,87,0,3,2,1,0
32,32,0,32,90,0,3,3,2,0
1,60,0,55,11,0,1,0,0,1
2,70,0,44,12,1,1,0,1,1
3,44,0,11,13,2,1,0,2,1
4,55,0,34,66,3,0,0,3,1
5,66,0,90,77,0,0,1,2,1
6,22,0,89,88,0,0,2,2,1
7,1,0,45,9,0,1,2,3,1
8,2,0,34,22,3,1,2,3,1
9,3,0,56,34,3,1,0,1,1
10,6,0,78,5,3,0,3,1,1
11,8,0,36,67,2,0,0,0,1
12,59,0,57,23,2,1,1,0,1
13,67,0,29,34,1,1,0,1,1
14,20,0,30,90,1,1,2,2,1
15,21,0,66,89,0,1,3,3,1
44,100,0,91,72,3,3,1,0,0
33,100,0,82,67,3,3,2,2,0
45,100,0,44,50,2,3,3,3,0
21,100,0,50,52,2,3,1,0,0
92,100,0,83,63,3,3,2,1,0
20,100,1,43,34,0,3,2,2,0
15,100,1,23,26,0,3,3,3,0
45,100,1,12,67,0,3,1,0,0
59,100,1,34,87,0,3,2,1,0
32,100,0,32,90,0,3,3,2,0
1,100,0,55,11,0,1,0,0,0
2,100,0,44,12,1,1,0,1,0
3,100,0,11,13,2,1,0,2,0
4,100,0,34,66,3,0,0,3,0
5,100,0,90,77,0,0,1,2,0
6,100,0,89,88,0,0,2,2,0
7,100,0,45,9,0,1,2,3,0
8,100,0,34,22,3,1,2,3,0
9,100,0,56,34,3,1,0,1,0
10,100,0,78,5,3,0,3,1,0
11,100,0,36,67,2,0,0,0,0
12,100,0,57,23,2,1,1,0,0
13,100,0,29,34,1,1,0,1,0
14,100,0,30,90,1,1,2,2,0
15,100,0,66,89,0,1,3,3,0
1,6,0,5,10,4,1,1,3,1
2,7,0,4,20,4,1,2,2,1
3,4,0,11,30,4,1,3,1,1
4,5,0,43,5,2,0,1,2,1
5,6,0,9,17,2,0,2,1,1
6,2,0,98,18,4,0,3,1,1
7,11,0,54,19,4,1,0,2,1
8,20,0,43,22,4,1,1,1,1
9,30,0,65,43,4,1,2,3,1
10,60,0,87,50,1,0,3,3,1
11,80,0,63,76,1,0,0,2,1
12,95,0,75,32,1,1,1,1,1
13,76,0,30,43,2,1,2,0,1
14,2,0,92,9,2,1,3,0,1
1,6,0,5,10,4,3,1,3,0
2,7,0,4,20,4,3,2,2,0
3,4,0,11,30,4,3,3,1,0
4,5,0,43,5,2,3,1,2,0
5,6,0,9,17,2,3,2,1,0
6,2,0,98,18,4,3,3,1,0
7,11,0,54,19,4,3,0,2,0
8,20,0,43,22,4,3,1,1,0
9,30,0,65,43,4,3,2,3,0
10,60,0,87,50,1,3,3,3,0
11,80,0,63,76,1,3,0,2,0
12,95,0,75,32,1,3,1,1,0
13,76,0,30,43,2,3,2,0,0
14,2,0,92,9,2,3,3,0,0
1 plant_water_level growth disease fertility tractor_water_level temperature rain season current_time action
2 1 20 0 40 60 2 0 2 1 1
3 20 40 0 40 60 2 0 2 1 1
4 87 20 0 40 60 2 0 2 1 0
5 27 43 1 40 60 2 0 2 1 0
6 89 56 1 40 60 2 1 1 1 0
7 67 100 1 37 55 1 3 3 3 0
8 67 40 1 87 90 4 0 1 0 0
9 1 20 0 40 60 2 0 0 1 0
10 20 40 0 40 60 2 0 0 1 0
11 87 20 0 56 45 2 0 0 2 0
12 27 43 1 40 60 2 0 0 3 0
13 89 56 1 40 89 2 1 0 1 0
14 67 100 1 37 55 1 3 0 3 0
15 67 40 1 87 90 4 0 0 0 0
16 1 100 0 45 20 2 0 2 1 0
17 20 100 0 40 34 0 1 2 0 0
18 87 100 0 56 60 2 0 1 1 0
19 27 100 0 89 67 1 2 2 2 0
20 89 100 0 40 60 2 1 1 1 0
21 76 100 0 37 55 1 3 3 3 0
22 67 100 0 87 90 4 0 1 0 0
23 1 20 0 40 0 2 0 2 1 0
24 20 40 0 40 0 2 0 2 1 0
25 87 20 0 40 0 2 0 2 1 0
26 27 43 1 40 0 2 0 2 1 0
27 89 56 1 40 0 2 1 1 1 0
28 67 100 1 37 0 1 3 3 3 0
29 67 40 1 87 0 4 0 1 0 0
30 1 20 0 40 0 2 0 0 1 0
31 20 40 0 40 0 2 0 0 1 0
32 87 20 0 56 0 2 0 0 2 0
33 27 43 1 40 0 2 0 0 3 0
34 89 56 1 40 0 2 1 0 1 0
35 67 100 1 37 0 1 3 0 3 0
36 67 40 1 87 0 4 0 0 0 0
37 1 100 0 45 0 2 0 2 1 0
38 20 100 0 40 0 0 1 2 0 0
39 87 100 0 56 0 2 0 1 1 0
40 27 100 0 89 0 1 2 2 2 0
41 89 100 0 40 0 2 1 1 1 0
42 76 100 0 37 0 1 3 3 3 0
43 67 100 0 87 0 4 0 1 0 0
44 1 45 0 56 44 2 1 1 1 1
45 20 55 0 43 34 2 0 2 2 1
46 15 23 0 23 26 2 1 3 3 1
47 45 67 0 12 67 3 0 1 0 1
48 59 88 0 34 87 3 0 2 1 1
49 32 32 0 32 90 3 0 3 2 1
50 44 43 0 19 27 2 0 1 3 1
51 33 11 0 28 76 2 0 2 0 1
52 54 90 0 44 5 3 0 3 1 1
53 21 76 0 50 25 3 1 1 2 1
54 29 64 0 38 36 2 0 2 3 1
55 11 54 0 65 44 3 1 1 2 1
56 23 55 0 34 43 3 0 2 1 1
57 51 32 0 32 62 3 1 3 3 1
58 54 76 0 21 76 2 0 1 2 1
59 95 88 0 43 78 2 0 2 1 0
60 23 23 0 23 9 2 0 3 3 1
61 44 34 0 91 72 3 0 1 0 1
62 33 11 0 82 67 3 0 2 2 1
63 45 9 0 44 50 2 0 3 3 1
64 21 67 0 50 52 2 1 1 0 1
65 92 46 0 83 63 3 0 2 1 0
66 20 55 1 43 34 0 0 2 2 0
67 15 23 1 23 26 0 1 3 3 0
68 45 67 1 12 67 0 0 1 0 0
69 59 88 1 34 87 0 0 2 1 0
70 32 32 0 32 90 0 0 3 2 0
71 44 43 0 19 27 4 0 1 3 0
72 33 11 0 28 76 4 0 2 0 0
73 54 90 0 44 5 4 0 3 1 0
74 21 76 0 50 25 4 1 1 2 0
75 29 64 0 38 36 4 0 2 3 0
76 11 54 0 65 44 0 1 1 2 0
77 23 55 0 34 43 0 0 2 1 0
78 51 32 0 32 62 0 1 3 3 0
79 80 76 1 39 7 3 0 1 0 0
80 98 77 0 15 91 1 3 2 3 0
81 3 48 1 73 41 2 2 0 3 0
82 20 15 1 97 87 4 1 2 1 0
83 93 6 0 37 0 0 1 0 1 0
84 4 31 0 1 5 2 3 1 2 0
85 42 52 0 33 19 3 2 3 0 0
86 76 43 0 77 18 4 0 0 3 0
87 31 13 1 21 42 0 1 2 3 0
88 96 65 1 63 35 1 3 3 2 0
89 29 39 0 40 37 3 3 0 0 0
90 82 53 0 55 9 0 1 3 2 0
91 21 35 0 58 1 1 2 2 0 0
92 92 98 0 69 16 3 0 0 1 0
93 34 23 0 95 2 2 3 0 3 0
94 36 28 0 62 22 0 1 1 1 0
95 66 88 1 10 85 3 1 2 3 0
96 53 51 0 79 90 2 2 3 2 0
97 9 74 0 60 4 4 1 2 3 1
98 17 0 0 38 58 1 2 3 0 0
99 12 76 0 50 25 3 1 1 2 1
100 92 64 0 38 36 2 0 2 3 0
101 11 54 0 65 44 3 1 1 2 1
102 32 55 0 34 43 3 0 2 1 1
103 15 32 0 32 62 3 1 3 3 1
104 45 76 0 21 76 2 0 1 2 1
105 59 88 0 43 78 2 0 2 1 1
106 32 23 0 23 9 2 0 3 3 1
107 14 34 0 91 72 3 0 1 0 1
108 13 11 0 82 67 3 0 2 2 1
109 45 9 0 44 50 2 0 3 3 1
110 21 67 0 50 52 2 1 1 0 1
111 92 46 0 83 63 3 0 2 1 0
112 2 40 1 34 43 1 3 2 2 0
113 51 32 1 32 62 2 1 3 3 0
114 54 76 1 21 76 3 0 1 0 0
115 98 38 0 50 44 4 0 1 0 0
116 63 7 0 93 79 2 0 2 1 1
117 91 59 0 94 24 4 0 3 2 0
118 11 49 0 54 76 2 0 1 3 1
119 33 31 0 59 39 3 0 1 3 1
120 28 50 0 26 0 4 0 2 2 0
121 54 83 0 36 0 3 0 2 1 0
122 49 78 0 68 0 2 0 3 2 0
123 59 21 0 43 100 1 0 3 2 1
124 1 30 0 52 100 2 0 0 3 0
125 60 9 0 40 40 3 0 0 3 0
126 85 94 0 87 85 4 0 1 3 0
127 79 68 0 56 90 1 0 2 2 1
128 75 22 0 25 95 1 0 3 2 1
129 100 51 0 33 12 0 0 2 2 0
130 90 70 0 71 81 0 0 2 1 0
131 47 26 0 6 78 4 0 1 1 1
132 14 89 0 70 18 4 0 1 0 1
133 99 19 0 74 91 2 0 3 0 0
134 18 48 0 15 32 2 0 3 0 1
135 5 57 0 14 34 0 1 1 3 1
136 22 67 0 9 5 0 1 2 2 0
137 95 81 0 46 86 1 1 3 1 0
138 39 65 0 84 0 1 1 0 0 0
139 84 75 0 30 0 2 1 1 1 0
140 86 41 0 2 67 2 1 2 2 0
141 64 53 0 53 47 1 1 3 3 1
142 69 61 0 0 73 2 1 0 0 0
143 94 40 1 0 18 3 1 1 2 0
144 62 82 1 20 50 4 1 2 3 0
145 57 1 1 17 92 0 1 3 2 0
146 80 35 1 58 45 0 0 3 1 0
147 30 47 1 8 47 1 0 2 1 0
148 82 32 0 99 39 1 3 1 3 0
149 20 84 0 0 51 2 3 2 3 0
150 42 88 0 0 54 2 2 2 0 0
151 66 45 0 91 10 3 2 1 0 0
152 81 14 0 19 55 3 0 1 2 1
153 74 37 0 88 78 4 0 3 2 1
154 89 99 0 100 60 4 0 3 3 0
155 15 20 0 45 11 0 0 1 3 1
156 92 28 0 85 90 2 0 1 1 0
157 55 4 0 13 95 2 0 2 1 1
158 2 6 0 35 0 2 0 2 0 0
159 61 56 0 90 0 2 0 3 0 0
160 76 11 0 61 10 3 0 3 1 1
161 26 80 0 57 9 3 0 1 2 1
162 40 44 0 81 8 3 0 2 3 1
163 50 66 0 23 7 3 0 3 0 1
164 48 15 0 77 6 2 0 0 1 0
165 11 54 0 65 44 3 3 1 2 0
166 23 55 0 34 43 3 3 2 1 0
167 51 32 0 32 62 3 3 3 3 0
168 54 76 0 21 76 2 3 1 2 0
169 95 88 0 43 78 2 3 2 1 0
170 23 23 0 23 9 2 3 3 3 0
171 44 34 0 91 72 3 3 1 0 0
172 33 11 0 82 67 3 3 2 2 0
173 45 9 0 44 50 2 3 3 3 0
174 21 67 0 50 52 2 3 1 0 0
175 92 46 0 83 63 3 3 2 1 0
176 20 55 1 43 34 0 3 2 2 0
177 15 23 1 23 26 0 3 3 3 0
178 45 67 1 12 67 0 3 1 0 0
179 59 88 1 34 87 0 3 2 1 0
180 32 32 0 32 90 0 3 3 2 0
181 1 60 0 55 11 0 1 0 0 1
182 2 70 0 44 12 1 1 0 1 1
183 3 44 0 11 13 2 1 0 2 1
184 4 55 0 34 66 3 0 0 3 1
185 5 66 0 90 77 0 0 1 2 1
186 6 22 0 89 88 0 0 2 2 1
187 7 1 0 45 9 0 1 2 3 1
188 8 2 0 34 22 3 1 2 3 1
189 9 3 0 56 34 3 1 0 1 1
190 10 6 0 78 5 3 0 3 1 1
191 11 8 0 36 67 2 0 0 0 1
192 12 59 0 57 23 2 1 1 0 1
193 13 67 0 29 34 1 1 0 1 1
194 14 20 0 30 90 1 1 2 2 1
195 15 21 0 66 89 0 1 3 3 1
196 44 100 0 91 72 3 3 1 0 0
197 33 100 0 82 67 3 3 2 2 0
198 45 100 0 44 50 2 3 3 3 0
199 21 100 0 50 52 2 3 1 0 0
200 92 100 0 83 63 3 3 2 1 0
201 20 100 1 43 34 0 3 2 2 0
202 15 100 1 23 26 0 3 3 3 0
203 45 100 1 12 67 0 3 1 0 0
204 59 100 1 34 87 0 3 2 1 0
205 32 100 0 32 90 0 3 3 2 0
206 1 100 0 55 11 0 1 0 0 0
207 2 100 0 44 12 1 1 0 1 0
208 3 100 0 11 13 2 1 0 2 0
209 4 100 0 34 66 3 0 0 3 0
210 5 100 0 90 77 0 0 1 2 0
211 6 100 0 89 88 0 0 2 2 0
212 7 100 0 45 9 0 1 2 3 0
213 8 100 0 34 22 3 1 2 3 0
214 9 100 0 56 34 3 1 0 1 0
215 10 100 0 78 5 3 0 3 1 0
216 11 100 0 36 67 2 0 0 0 0
217 12 100 0 57 23 2 1 1 0 0
218 13 100 0 29 34 1 1 0 1 0
219 14 100 0 30 90 1 1 2 2 0
220 15 100 0 66 89 0 1 3 3 0
221 1 6 0 5 10 4 1 1 3 1
222 2 7 0 4 20 4 1 2 2 1
223 3 4 0 11 30 4 1 3 1 1
224 4 5 0 43 5 2 0 1 2 1
225 5 6 0 9 17 2 0 2 1 1
226 6 2 0 98 18 4 0 3 1 1
227 7 11 0 54 19 4 1 0 2 1
228 8 20 0 43 22 4 1 1 1 1
229 9 30 0 65 43 4 1 2 3 1
230 10 60 0 87 50 1 0 3 3 1
231 11 80 0 63 76 1 0 0 2 1
232 12 95 0 75 32 1 1 1 1 1
233 13 76 0 30 43 2 1 2 0 1
234 14 2 0 92 9 2 1 3 0 1
235 1 6 0 5 10 4 3 1 3 0
236 2 7 0 4 20 4 3 2 2 0
237 3 4 0 11 30 4 3 3 1 0
238 4 5 0 43 5 2 3 1 2 0
239 5 6 0 9 17 2 3 2 1 0
240 6 2 0 98 18 4 3 3 1 0
241 7 11 0 54 19 4 3 0 2 0
242 8 20 0 43 22 4 3 1 1 0
243 9 30 0 65 43 4 3 2 3 0
244 10 60 0 87 50 1 3 3 3 0
245 11 80 0 63 76 1 3 0 2 0
246 12 95 0 75 32 1 3 1 1 0
247 13 76 0 30 43 2 3 2 0 0
248 14 2 0 92 9 2 3 3 0 0

1
Drzewo.py
View File

@ -9,6 +9,7 @@ class Drzewo:
def treeLearn(self): def treeLearn(self):
csvdata=pandas.read_csv('Data/dataTree.csv') csvdata=pandas.read_csv('Data/dataTree.csv')
#csvdata = pandas.read_csv('Data/dataTree2.csv')
x=csvdata[atributes] x=csvdata[atributes]
decision=csvdata['action'] decision=csvdata['action']
self.tree=skltree.DecisionTreeClassifier() self.tree=skltree.DecisionTreeClassifier()