digraph Tree {
node [shape=box, style="filled, rounded", color="black", fontname=FangSong] ;
edge [fontname=FangSong] ;
0 [label=<体重 ≤ 0.46
gini = 0.86
samples = 1302
value = [265, 285, 339, 297, 339, 271, 291]
class = Obesity_Type_I>, fillcolor="#ffffff"] ;
1 [label=<家庭状况 ≤ 0.5
gini = 0.8
samples = 845
value = [265, 285, 233, 4, 0, 271, 288]
class = Overweight_Level_II>, fillcolor="#fffeff"] ;
0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
2 [label=<体重 ≤ 0.09
gini = 0.68
samples = 226
value = [142, 142, 2, 2, 0, 58, 26]
class = Insufficient_Weight>, fillcolor="#ffffff"] ;
1 -> 2 ;
3 [label=<蔬菜食用频率 ≤ 0.5
gini = 0.24
samples = 91
value = [132, 22, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e9965a"] ;
2 -> 3 ;
4 [label=<年龄 ≤ 0.13
gini = 0.44
samples = 32
value = [38, 19, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#f2c09c"] ;
3 -> 4 ;
5 [label=<酒精消耗量 ≤ 0.17
gini = 0.29
samples = 28
value = [38, 8, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#ea9c63"] ;
4 -> 5 ;
6 [label=samples = 2
value = [0, 4, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
5 -> 6 ;
7 [label=<年龄 ≤ 0.05
gini = 0.17
samples = 26
value = [38, 4, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e88e4e"] ;
5 -> 7 ;
8 [label=samples = 1
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
7 -> 8 ;
9 [label=<年龄 ≤ 0.07
gini = 0.09
samples = 25
value = [38, 2, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e68843"] ;
7 -> 9 ;
10 [label=<蔬菜食用频率 ≤ 0.25
gini = 0.44
samples = 2
value = [2, 1, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#f2c09c"] ;
9 -> 10 ;
11 [label=samples = 1
value = [0, 1, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
10 -> 11 ;
12 [label=samples = 1
value = [2, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
10 -> 12 ;
13 [label=<蔬菜食用频率 ≤ 0.47
gini = 0.05
samples = 23
value = [36, 1, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e6843e"] ;
9 -> 13 ;
14 [label=samples = 21
value = [35, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
13 -> 14 ;
15 [label=<年龄 ≤ 0.1
gini = 0.5
samples = 2
value = [1, 1, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#ffffff"] ;
13 -> 15 ;
16 [label=samples = 1
value = [0, 1, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
15 -> 16 ;
17 [label=samples = 1
value = [1, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
15 -> 17 ;
18 [label=samples = 4
value = [0, 11, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
4 -> 18 ;
19 [label=<年龄 ≤ 0.2
gini = 0.06
samples = 59
value = [94, 3, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e6853f"] ;
3 -> 19 ;
20 [label=<每日水消耗量 ≤ 0.0
gini = 0.04
samples = 57
value = [93, 2, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e6843d"] ;
19 -> 20 ;
21 [label=<两餐之间的食物消耗量 ≤ 0.5
gini = 0.24
samples = 9
value = [12, 2, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e9965a"] ;
20 -> 21 ;
22 [label=samples = 1
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
21 -> 22 ;
23 [label=samples = 8
value = [12, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
21 -> 23 ;
24 [label=samples = 48
value = [81, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
20 -> 24 ;
25 [label=<年龄 ≤ 0.37
gini = 0.5
samples = 2
value = [1, 1, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#ffffff"] ;
19 -> 25 ;
26 [label=samples = 1
value = [0, 1, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
25 -> 26 ;
27 [label=samples = 1
value = [1, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
25 -> 27 ;
28 [label=<年龄 ≤ 0.26
gini = 0.61
samples = 135
value = [10, 120, 2, 2, 0, 58, 26]
class = Normal_Weight>, fillcolor="#e3f5b2"] ;
2 -> 28 ;
29 [label=<体重 ≤ 0.3
gini = 0.56
samples = 106
value = [10, 107, 1, 2, 0, 35, 17]
class = Normal_Weight>, fillcolor="#d9f197"] ;
28 -> 29 ;
30 [label=<酒精消耗量 ≤ 0.5
gini = 0.46
samples = 94
value = [10, 103, 0, 0, 0, 33, 2]
class = Normal_Weight>, fillcolor="#d3ef86"] ;
29 -> 30 ;
31 [label=<两餐之间的食物消耗量 ≤ 0.5
gini = 0.21
samples = 36
value = [3, 53, 0, 0, 0, 4, 0]
class = Normal_Weight>, fillcolor="#c0e852"] ;
30 -> 31 ;
32 [label=<身高 ≤ 0.82
gini = 0.16
samples = 27
value = [1, 43, 0, 0, 0, 3, 0]
class = Normal_Weight>, fillcolor="#bee74b"] ;
31 -> 32 ;
33 [label=<身高 ≤ 0.33
gini = 0.12
samples = 26
value = [0, 43, 0, 0, 0, 3, 0]
class = Normal_Weight>, fillcolor="#bce747"] ;
32 -> 33 ;
34 [label=<身高 ≤ 0.3
gini = 0.38
samples = 7
value = [0, 9, 0, 0, 0, 3, 0]
class = Normal_Weight>, fillcolor="#cfee7b"] ;
33 -> 34 ;
35 [label=<体重 ≤ 0.17
gini = 0.22
samples = 5
value = [0, 7, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#c1e955"] ;
34 -> 35 ;
36 [label=samples = 4
value = [0, 7, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
35 -> 36 ;
37 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
35 -> 37 ;
38 [label=<体重 ≤ 0.18
gini = 0.5
samples = 2
value = [0, 2, 0, 0, 0, 2, 0]
class = Normal_Weight>, fillcolor="#ffffff"] ;
34 -> 38 ;
39 [label=samples = 1
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
38 -> 39 ;
40 [label=samples = 1
value = [0, 0, 0, 0, 0, 2, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
38 -> 40 ;
41 [label=samples = 19
value = [0, 34, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
33 -> 41 ;
42 [label=samples = 1
value = [1, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
32 -> 42 ;
43 [label=<身高 ≤ 0.1
gini = 0.38
samples = 9
value = [2, 10, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#cbec6f"] ;
31 -> 43 ;
44 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
43 -> 44 ;
45 [label=<体重 ≤ 0.15
gini = 0.28
samples = 8
value = [2, 10, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#c5ea61"] ;
43 -> 45 ;
46 [label=<蔬菜食用频率 ≤ 0.75
gini = 0.48
samples = 4
value = [2, 3, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#e7f6bd"] ;
45 -> 46 ;
47 [label=samples = 2
value = [2, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
46 -> 47 ;
48 [label=samples = 2
value = [0, 3, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
46 -> 48 ;
49 [label=samples = 4
value = [0, 7, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
45 -> 49 ;
50 [label=<身高 ≤ 0.36
gini = 0.56
samples = 58
value = [7, 50, 0, 0, 0, 29, 2]
class = Normal_Weight>, fillcolor="#e5f6b9"] ;
30 -> 50 ;
51 [label=<每日水消耗量 ≤ 0.01
gini = 0.47
samples = 27
value = [0, 12, 0, 0, 0, 28, 2]
class = Overweight_Level_I>, fillcolor="#d595f1"] ;
50 -> 51 ;
52 [label=samples = 2
value = [0, 3, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
51 -> 52 ;
53 [label=<每日水消耗量 ≤ 0.49
gini = 0.43
samples = 25
value = [0, 9, 0, 0, 0, 28, 2]
class = Overweight_Level_I>, fillcolor="#ce82ef"] ;
51 -> 53 ;
54 [label=samples = 10
value = [0, 0, 0, 0, 0, 14, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
53 -> 54 ;
55 [label=<体重 ≤ 0.18
gini = 0.55
samples = 15
value = [0, 9, 0, 0, 0, 14, 2]
class = Overweight_Level_I>, fillcolor="#e7c1f7"] ;
53 -> 55 ;
56 [label=<卡路里消耗 ≤ 0.5
gini = 0.18
samples = 7
value = [0, 9, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#bfe84f"] ;
55 -> 56 ;
57 [label=samples = 6
value = [0, 9, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
56 -> 57 ;
58 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
56 -> 58 ;
59 [label=<体重 ≤ 0.25
gini = 0.23
samples = 8
value = [0, 0, 0, 0, 0, 13, 2]
class = Overweight_Level_I>, fillcolor="#bd57e9"] ;
55 -> 59 ;
60 [label=samples = 7
value = [0, 0, 0, 0, 0, 13, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
59 -> 60 ;
61 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 2]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
59 -> 61 ;
62 [label=<体重 ≤ 0.1
gini = 0.29
samples = 31
value = [7, 38, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#c6ea62"] ;
50 -> 62 ;
63 [label=samples = 6
value = [7, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
62 -> 63 ;
64 [label=<体重 ≤ 0.25
gini = 0.05
samples = 25
value = [0, 38, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#b9e63e"] ;
62 -> 64 ;
65 [label=samples = 21
value = [0, 32, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
64 -> 65 ;
66 [label=<蔬菜食用频率 ≤ 0.75
gini = 0.24
samples = 4
value = [0, 6, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#c3e95a"] ;
64 -> 66 ;
67 [label=samples = 2
value = [0, 4, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
66 -> 67 ;
68 [label=<两餐之间的食物消耗量 ≤ 0.17
gini = 0.44
samples = 2
value = [0, 2, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#dbf29c"] ;
66 -> 68 ;
69 [label=samples = 1
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
68 -> 69 ;
70 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
68 -> 70 ;
71 [label=<蔬菜食用频率 ≤ 0.25
gini = 0.57
samples = 12
value = [0, 4, 1, 2, 0, 2, 15]
class = Overweight_Level_II>, fillcolor="#f192bc"] ;
29 -> 71 ;
72 [label=samples = 1
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
71 -> 72 ;
73 [label=<两餐之间的食物消耗量 ≤ 0.17
gini = 0.51
samples = 11
value = [0, 2, 1, 2, 0, 2, 15]
class = Overweight_Level_II>, fillcolor="#ee7eb0"] ;
71 -> 73 ;
74 [label=<体重 ≤ 0.36
gini = 0.44
samples = 2
value = [0, 1, 0, 2, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#9cf2f0"] ;
73 -> 74 ;
75 [label=samples = 1
value = [0, 1, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
74 -> 75 ;
76 [label=samples = 1
value = [0, 0, 0, 2, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#39e5e2"] ;
74 -> 76 ;
77 [label=<身高 ≤ 0.73
gini = 0.36
samples = 9
value = [0, 1, 1, 0, 0, 2, 15]
class = Overweight_Level_II>, fillcolor="#eb68a2"] ;
73 -> 77 ;
78 [label=<年龄 ≤ 0.24
gini = 0.29
samples = 8
value = [0, 0, 1, 0, 0, 2, 15]
class = Overweight_Level_II>, fillcolor="#ea5e9d"] ;
77 -> 78 ;
79 [label=<年龄 ≤ 0.13
gini = 0.12
samples = 7
value = [0, 0, 1, 0, 0, 0, 15]
class = Overweight_Level_II>, fillcolor="#e7468e"] ;
78 -> 79 ;
80 [label=<高热量食物 ≤ 0.5
gini = 0.38
samples = 2
value = [0, 0, 1, 0, 0, 0, 3]
class = Overweight_Level_II>, fillcolor="#ee7bae"] ;
79 -> 80 ;
81 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 3]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
80 -> 81 ;
82 [label=samples = 1
value = [0, 0, 1, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
80 -> 82 ;
83 [label=samples = 5
value = [0, 0, 0, 0, 0, 0, 12]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
79 -> 83 ;
84 [label=samples = 1
value = [0, 0, 0, 0, 0, 2, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
78 -> 84 ;
85 [label=samples = 1
value = [0, 1, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
77 -> 85 ;
86 [label=<每日水消耗量 ≤ 0.46
gini = 0.63
samples = 29
value = [0, 13, 1, 0, 0, 23, 9]
class = Overweight_Level_I>, fillcolor="#e7c3f7"] ;
28 -> 86 ;
87 [label=<年龄 ≤ 0.61
gini = 0.1
samples = 11
value = [0, 0, 0, 0, 0, 18, 1]
class = Overweight_Level_I>, fillcolor="#b544e6"] ;
86 -> 87 ;
88 [label=samples = 10
value = [0, 0, 0, 0, 0, 18, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
87 -> 88 ;
89 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 1]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
87 -> 89 ;
90 [label=<体重 ≤ 0.27
gini = 0.64
samples = 18
value = [0, 13, 1, 0, 0, 5, 8]
class = Normal_Weight>, fillcolor="#ecf8cb"] ;
86 -> 90 ;
91 [label=samples = 6
value = [0, 10, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
90 -> 91 ;
92 [label=<体重 ≤ 0.32
gini = 0.66
samples = 12
value = [0, 3, 1, 0, 0, 5, 8]
class = Overweight_Level_II>, fillcolor="#f8cee1"] ;
90 -> 92 ;
93 [label=<身高 ≤ 0.26
gini = 0.22
samples = 6
value = [0, 0, 1, 0, 0, 0, 7]
class = Overweight_Level_II>, fillcolor="#e95597"] ;
92 -> 93 ;
94 [label=samples = 1
value = [0, 0, 1, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
93 -> 94 ;
95 [label=samples = 5
value = [0, 0, 0, 0, 0, 0, 7]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
93 -> 95 ;
96 [label=<身高 ≤ 0.72
gini = 0.57
samples = 6
value = [0, 3, 0, 0, 0, 5, 1]
class = Overweight_Level_I>, fillcolor="#e5bdf6"] ;
92 -> 96 ;
97 [label=<高热量食物 ≤ 0.5
gini = 0.28
samples = 5
value = [0, 0, 0, 0, 0, 5, 1]
class = Overweight_Level_I>, fillcolor="#c161ea"] ;
96 -> 97 ;
98 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 1]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
97 -> 98 ;
99 [label=samples = 4
value = [0, 0, 0, 0, 0, 5, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
97 -> 99 ;
100 [label=samples = 1
value = [0, 3, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
96 -> 100 ;
101 [label=<体重 ≤ 0.28
gini = 0.79
samples = 619
value = [123, 143, 231, 2, 0, 213, 262]
class = Overweight_Level_II>, fillcolor="#fef7fa"] ;
1 -> 101 ;
102 [label=<体重 ≤ 0.16
gini = 0.72
samples = 270
value = [123, 128, 5, 0, 0, 139, 38]
class = Overweight_Level_I>, fillcolor="#fcf8fe"] ;
101 -> 102 ;
103 [label=<身高 ≤ 0.4
gini = 0.46
samples = 116
value = [116, 58, 0, 0, 0, 2, 0]
class = Insufficient_Weight>, fillcolor="#f2c19e"] ;
102 -> 103 ;
104 [label=<两餐之间的食物消耗量 ≤ 0.83
gini = 0.24
samples = 35
value = [5, 45, 0, 0, 0, 2, 0]
class = Normal_Weight>, fillcolor="#c2e956"] ;
103 -> 104 ;
105 [label=<每日水消耗量 ≤ 0.55
gini = 0.19
samples = 33
value = [3, 44, 0, 0, 0, 2, 0]
class = Normal_Weight>, fillcolor="#bfe84f"] ;
104 -> 105 ;
106 [label=<年龄 ≤ 0.49
gini = 0.1
samples = 25
value = [0, 37, 0, 0, 0, 2, 0]
class = Normal_Weight>, fillcolor="#bbe644"] ;
105 -> 106 ;
107 [label=<身高 ≤ 0.13
gini = 0.05
samples = 23
value = [0, 35, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#b9e63f"] ;
106 -> 107 ;
108 [label=<两餐之间的食物消耗量 ≤ 0.5
gini = 0.38
samples = 3
value = [0, 3, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#cfee7b"] ;
107 -> 108 ;
109 [label=samples = 2
value = [0, 3, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
108 -> 109 ;
110 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
108 -> 110 ;
111 [label=samples = 20
value = [0, 32, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
107 -> 111 ;
112 [label=<身高 ≤ 0.23
gini = 0.44
samples = 2
value = [0, 2, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#dbf29c"] ;
106 -> 112 ;
113 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
112 -> 113 ;
114 [label=samples = 1
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
112 -> 114 ;
115 [label=<体重 ≤ 0.07
gini = 0.42
samples = 8
value = [3, 7, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#d6f08e"] ;
105 -> 115 ;
116 [label=samples = 3
value = [3, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
115 -> 116 ;
117 [label=samples = 5
value = [0, 7, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
115 -> 117 ;
118 [label=<年龄 ≤ 0.16
gini = 0.44
samples = 2
value = [2, 1, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#f2c09c"] ;
104 -> 118 ;
119 [label=samples = 1
value = [0, 1, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
118 -> 119 ;
120 [label=samples = 1
value = [2, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
118 -> 120 ;
121 [label=<身高 ≤ 0.48
gini = 0.19
samples = 81
value = [111, 13, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e89050"] ;
103 -> 121 ;
122 [label=<身高 ≤ 0.47
gini = 0.46
samples = 14
value = [14, 8, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#f4c9aa"] ;
121 -> 122 ;
123 [label=<体重 ≤ 0.12
gini = 0.12
samples = 11
value = [14, 1, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e78a47"] ;
122 -> 123 ;
124 [label=samples = 10
value = [14, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
123 -> 124 ;
125 [label=samples = 1
value = [0, 1, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
123 -> 125 ;
126 [label=samples = 3
value = [0, 7, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
122 -> 126 ;
127 [label=<两餐之间的食物消耗量 ≤ 0.83
gini = 0.09
samples = 67
value = [97, 5, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e68743"] ;
121 -> 127 ;
128 [label=<每日水消耗量 ≤ 0.01
gini = 0.06
samples = 66
value = [97, 3, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e6853f"] ;
127 -> 128 ;
129 [label=<高热量食物 ≤ 0.5
gini = 0.44
samples = 3
value = [1, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#dbf29c"] ;
128 -> 129 ;
130 [label=samples = 1
value = [1, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
129 -> 130 ;
131 [label=samples = 2
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
129 -> 131 ;
132 [label=<两餐之间的食物消耗量 ≤ 0.5
gini = 0.02
samples = 63
value = [96, 1, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e5823b"] ;
128 -> 132 ;
133 [label=samples = 43
value = [68, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
132 -> 133 ;
134 [label=<年龄 ≤ 0.08
gini = 0.07
samples = 20
value = [28, 1, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e68640"] ;
132 -> 134 ;
135 [label=samples = 1
value = [0, 1, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
134 -> 135 ;
136 [label=samples = 19
value = [28, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
134 -> 136 ;
137 [label=samples = 1
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
127 -> 137 ;
138 [label=<酒精消耗量 ≤ 0.5
gini = 0.62
samples = 154
value = [7, 70, 5, 0, 0, 137, 38]
class = Overweight_Level_I>, fillcolor="#e3b8f6"] ;
102 -> 138 ;
139 [label=<年龄 ≤ 0.1
gini = 0.65
samples = 56
value = [0, 39, 0, 0, 0, 23, 30]
class = Normal_Weight>, fillcolor="#f5fbe2"] ;
138 -> 139 ;
140 [label=<蔬菜食用频率 ≤ 0.98
gini = 0.31
samples = 16
value = [0, 3, 0, 0, 0, 23, 2]
class = Overweight_Level_I>, fillcolor="#c161ea"] ;
139 -> 140 ;
141 [label=samples = 12
value = [0, 0, 0, 0, 0, 22, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
140 -> 141 ;
142 [label=<体重 ≤ 0.23
gini = 0.61
samples = 4
value = [0, 3, 0, 0, 0, 1, 2]
class = Normal_Weight>, fillcolor="#edf8ce"] ;
140 -> 142 ;
143 [label=samples = 2
value = [0, 3, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
142 -> 143 ;
144 [label=<身高 ≤ 0.35
gini = 0.44
samples = 2
value = [0, 0, 0, 0, 0, 1, 2]
class = Overweight_Level_II>, fillcolor="#f29cc2"] ;
142 -> 144 ;
145 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 2]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
144 -> 145 ;
146 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
144 -> 146 ;
147 [label=<身高 ≤ 0.26
gini = 0.49
samples = 40
value = [0, 36, 0, 0, 0, 0, 28]
class = Normal_Weight>, fillcolor="#eff9d3"] ;
139 -> 147 ;
148 [label=samples = 19
value = [0, 0, 0, 0, 0, 0, 26]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
147 -> 148 ;
149 [label=<年龄 ≤ 0.14
gini = 0.1
samples = 21
value = [0, 36, 0, 0, 0, 0, 2]
class = Normal_Weight>, fillcolor="#bbe644"] ;
147 -> 149 ;
150 [label=<体重 ≤ 0.25
gini = 0.38
samples = 5
value = [0, 6, 0, 0, 0, 0, 2]
class = Normal_Weight>, fillcolor="#cfee7b"] ;
149 -> 150 ;
151 [label=samples = 4
value = [0, 6, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
150 -> 151 ;
152 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 2]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
150 -> 152 ;
153 [label=samples = 16
value = [0, 30, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
149 -> 153 ;
154 [label=<身高 ≤ 0.51
gini = 0.48
samples = 98
value = [7, 31, 5, 0, 0, 114, 8]
class = Overweight_Level_I>, fillcolor="#cf84ef"] ;
138 -> 154 ;
155 [label=<年龄 ≤ 0.14
gini = 0.29
samples = 76
value = [0, 9, 5, 0, 0, 111, 8]
class = Overweight_Level_I>, fillcolor="#bf5cea"] ;
154 -> 155 ;
156 [label=<卡路里消耗 ≤ 0.5
gini = 0.48
samples = 12
value = [0, 0, 0, 0, 0, 11, 7]
class = Overweight_Level_I>, fillcolor="#e3b7f6"] ;
155 -> 156 ;
157 [label=samples = 6
value = [0, 0, 0, 0, 0, 0, 7]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
156 -> 157 ;
158 [label=samples = 6
value = [0, 0, 0, 0, 0, 11, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
156 -> 158 ;
159 [label=<身高 ≤ 0.16
gini = 0.24
samples = 64
value = [0, 9, 5, 0, 0, 100, 1]
class = Overweight_Level_I>, fillcolor="#bc55e9"] ;
155 -> 159 ;
160 [label=<蔬菜食用频率 ≤ 0.51
gini = 0.41
samples = 5
value = [0, 0, 5, 0, 0, 2, 0]
class = Obesity_Type_I>, fillcolor="#88ef94"] ;
159 -> 160 ;
161 [label=samples = 4
value = [0, 0, 5, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
160 -> 161 ;
162 [label=samples = 1
value = [0, 0, 0, 0, 0, 2, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
160 -> 162 ;
163 [label=<酒精消耗量 ≤ 0.83
gini = 0.17
samples = 59
value = [0, 9, 0, 0, 0, 98, 1]
class = Overweight_Level_I>, fillcolor="#b94de8"] ;
159 -> 163 ;
164 [label=<蔬菜食用频率 ≤ 0.99
gini = 0.14
samples = 58
value = [0, 7, 0, 0, 0, 98, 1]
class = Overweight_Level_I>, fillcolor="#b749e7"] ;
163 -> 164 ;
165 [label=<每日水消耗量 ≤ 0.0
gini = 0.04
samples = 49
value = [0, 1, 0, 0, 0, 88, 1]
class = Overweight_Level_I>, fillcolor="#b33de6"] ;
164 -> 165 ;
166 [label=<体重 ≤ 0.24
gini = 0.32
samples = 5
value = [0, 1, 0, 0, 0, 4, 0]
class = Overweight_Level_I>, fillcolor="#c46aec"] ;
165 -> 166 ;
167 [label=samples = 1
value = [0, 1, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
166 -> 167 ;
168 [label=samples = 4
value = [0, 0, 0, 0, 0, 4, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
166 -> 168 ;
169 [label=<高热量食物 ≤ 0.5
gini = 0.02
samples = 44
value = [0, 0, 0, 0, 0, 84, 1]
class = Overweight_Level_I>, fillcolor="#b23be5"] ;
165 -> 169 ;
170 [label=<身高 ≤ 0.27
gini = 0.28
samples = 3
value = [0, 0, 0, 0, 0, 5, 1]
class = Overweight_Level_I>, fillcolor="#c161ea"] ;
169 -> 170 ;
171 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 1]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
170 -> 171 ;
172 [label=samples = 2
value = [0, 0, 0, 0, 0, 5, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
170 -> 172 ;
173 [label=samples = 41
value = [0, 0, 0, 0, 0, 79, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
169 -> 173 ;
174 [label=<高热量食物 ≤ 0.5
gini = 0.47
samples = 9
value = [0, 6, 0, 0, 0, 10, 0]
class = Overweight_Level_I>, fillcolor="#e0b0f5"] ;
164 -> 174 ;
175 [label=samples = 5
value = [0, 0, 0, 0, 0, 9, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
174 -> 175 ;
176 [label=<身高 ≤ 0.45
gini = 0.24
samples = 4
value = [0, 6, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#c3e95a"] ;
174 -> 176 ;
177 [label=samples = 3
value = [0, 6, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
176 -> 177 ;
178 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
176 -> 178 ;
179 [label=samples = 1
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
163 -> 179 ;
180 [label=<身高 ≤ 0.74
gini = 0.47
samples = 22
value = [7, 22, 0, 0, 0, 3, 0]
class = Normal_Weight>, fillcolor="#d4ef88"] ;
154 -> 180 ;
181 [label=<蔬菜食用频率 ≤ 0.25
gini = 0.21
samples = 18
value = [0, 22, 0, 0, 0, 3, 0]
class = Normal_Weight>, fillcolor="#c1e954"] ;
180 -> 181 ;
182 [label=samples = 4
value = [0, 6, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
181 -> 182 ;
183 [label=<体重 ≤ 0.27
gini = 0.27
samples = 14
value = [0, 16, 0, 0, 0, 3, 0]
class = Normal_Weight>, fillcolor="#c4ea5e"] ;
181 -> 183 ;
184 [label=<年龄 ≤ 0.31
gini = 0.12
samples = 11
value = [0, 15, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#bce746"] ;
183 -> 184 ;
185 [label=samples = 10
value = [0, 15, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
184 -> 185 ;
186 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
184 -> 186 ;
187 [label=<高热量食物 ≤ 0.5
gini = 0.44
samples = 3
value = [0, 1, 0, 0, 0, 2, 0]
class = Overweight_Level_I>, fillcolor="#d89cf2"] ;
183 -> 187 ;
188 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
187 -> 188 ;
189 [label=<体重 ≤ 0.27
gini = 0.5
samples = 2
value = [0, 1, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#ffffff"] ;
187 -> 189 ;
190 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
189 -> 190 ;
191 [label=samples = 1
value = [0, 1, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
189 -> 191 ;
192 [label=samples = 4
value = [7, 0, 0, 0, 0, 0, 0]
class = Insufficient_Weight>, fillcolor="#e58139"] ;
180 -> 192 ;
193 [label=<身高 ≤ 0.38
gini = 0.63
samples = 349
value = [0, 15, 226, 2, 0, 74, 224]
class = Obesity_Type_I>, fillcolor="#fefffe"] ;
101 -> 193 ;
194 [label=<体重 ≤ 0.42
gini = 0.08
samples = 75
value = [0, 0, 120, 2, 0, 0, 3]
class = Obesity_Type_I>, fillcolor="#41e654"] ;
193 -> 194 ;
195 [label=<年龄 ≤ 0.65
gini = 0.05
samples = 73
value = [0, 0, 120, 0, 0, 0, 3]
class = Obesity_Type_I>, fillcolor="#3ee651"] ;
194 -> 195 ;
196 [label=<身高 ≤ 0.35
gini = 0.03
samples = 71
value = [0, 0, 119, 0, 0, 0, 2]
class = Obesity_Type_I>, fillcolor="#3ce550"] ;
195 -> 196 ;
197 [label=samples = 63
value = [0, 0, 108, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
196 -> 197 ;
198 [label=<蔬菜食用频率 ≤ 0.85
gini = 0.26
samples = 8
value = [0, 0, 11, 0, 0, 0, 2]
class = Obesity_Type_I>, fillcolor="#5dea6d"] ;
196 -> 198 ;
199 [label=samples = 7
value = [0, 0, 11, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
198 -> 199 ;
200 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 2]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
198 -> 200 ;
201 [label=<体重 ≤ 0.3
gini = 0.5
samples = 2
value = [0, 0, 1, 0, 0, 0, 1]
class = Obesity_Type_I>, fillcolor="#ffffff"] ;
195 -> 201 ;
202 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 1]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
201 -> 202 ;
203 [label=samples = 1
value = [0, 0, 1, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
201 -> 203 ;
204 [label=samples = 2
value = [0, 0, 0, 2, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#39e5e2"] ;
194 -> 204 ;
205 [label=<年龄 ≤ 0.2
gini = 0.62
samples = 274
value = [0, 15, 106, 0, 0, 74, 221]
class = Overweight_Level_II>, fillcolor="#f5b6d2"] ;
193 -> 205 ;
206 [label=<酒精消耗量 ≤ 0.17
gini = 0.69
samples = 164
value = [0, 12, 81, 0, 0, 63, 88]
class = Overweight_Level_II>, fillcolor="#fef6fa"] ;
205 -> 206 ;
207 [label=<体重 ≤ 0.33
gini = 0.53
samples = 66
value = [0, 2, 63, 0, 0, 7, 30]
class = Obesity_Type_I>, fillcolor="#a4f3ad"] ;
206 -> 207 ;
208 [label=<身高 ≤ 0.54
gini = 0.38
samples = 23
value = [0, 2, 0, 0, 0, 7, 29]
class = Overweight_Level_II>, fillcolor="#ed72a9"] ;
207 -> 208 ;
209 [label=samples = 17
value = [0, 0, 0, 0, 0, 0, 29]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
208 -> 209 ;
210 [label=<身高 ≤ 0.66
gini = 0.35
samples = 6
value = [0, 2, 0, 0, 0, 7, 0]
class = Overweight_Level_I>, fillcolor="#c772ec"] ;
208 -> 210 ;
211 [label=samples = 5
value = [0, 0, 0, 0, 0, 7, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
210 -> 211 ;
212 [label=samples = 1
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
210 -> 212 ;
213 [label=<高热量食物 ≤ 0.5
gini = 0.03
samples = 43
value = [0, 0, 63, 0, 0, 0, 1]
class = Obesity_Type_I>, fillcolor="#3ce550"] ;
207 -> 213 ;
214 [label=<身高 ≤ 0.52
gini = 0.5
samples = 2
value = [0, 0, 1, 0, 0, 0, 1]
class = Obesity_Type_I>, fillcolor="#ffffff"] ;
213 -> 214 ;
215 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 1]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
214 -> 215 ;
216 [label=samples = 1
value = [0, 0, 1, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
214 -> 216 ;
217 [label=samples = 41
value = [0, 0, 62, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
213 -> 217 ;
218 [label=<身高 ≤ 0.53
gini = 0.66
samples = 98
value = [0, 10, 18, 0, 0, 56, 58]
class = Overweight_Level_II>, fillcolor="#fefafc"] ;
206 -> 218 ;
219 [label=<每日水消耗量 ≤ 0.24
gini = 0.48
samples = 31
value = [0, 0, 17, 0, 0, 0, 26]
class = Overweight_Level_II>, fillcolor="#f6bad5"] ;
218 -> 219 ;
220 [label=samples = 6
value = [0, 0, 7, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
219 -> 220 ;
221 [label=<体重 ≤ 0.36
gini = 0.4
samples = 25
value = [0, 0, 10, 0, 0, 0, 26]
class = Overweight_Level_II>, fillcolor="#ef85b5"] ;
219 -> 221 ;
222 [label=<每日水消耗量 ≤ 0.8
gini = 0.13
samples = 19
value = [0, 0, 2, 0, 0, 0, 26]
class = Overweight_Level_II>, fillcolor="#e7488f"] ;
221 -> 222 ;
223 [label=samples = 15
value = [0, 0, 0, 0, 0, 0, 22]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
222 -> 223 ;
224 [label=<蔬菜食用频率 ≤ 0.3
gini = 0.44
samples = 4
value = [0, 0, 2, 0, 0, 0, 4]
class = Overweight_Level_II>, fillcolor="#f29cc2"] ;
222 -> 224 ;
225 [label=samples = 1
value = [0, 0, 2, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
224 -> 225 ;
226 [label=samples = 3
value = [0, 0, 0, 0, 0, 0, 4]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
224 -> 226 ;
227 [label=samples = 6
value = [0, 0, 8, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
221 -> 227 ;
228 [label=<年龄 ≤ 0.09
gini = 0.57
samples = 67
value = [0, 10, 1, 0, 0, 56, 32]
class = Overweight_Level_I>, fillcolor="#e3b8f6"] ;
218 -> 228 ;
229 [label=<两餐之间的食物消耗量 ≤ 0.5
gini = 0.3
samples = 11
value = [0, 2, 0, 0, 0, 1, 14]
class = Overweight_Level_II>, fillcolor="#ea619e"] ;
228 -> 229 ;
230 [label=<酒精消耗量 ≤ 0.5
gini = 0.12
samples = 10
value = [0, 0, 0, 0, 0, 1, 14]
class = Overweight_Level_II>, fillcolor="#e7478f"] ;
229 -> 230 ;
231 [label=<体重 ≤ 0.33
gini = 0.44
samples = 2
value = [0, 0, 0, 0, 0, 1, 2]
class = Overweight_Level_II>, fillcolor="#f29cc2"] ;
230 -> 231 ;
232 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
231 -> 232 ;
233 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 2]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
231 -> 233 ;
234 [label=samples = 8
value = [0, 0, 0, 0, 0, 0, 12]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
230 -> 234 ;
235 [label=samples = 1
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
229 -> 235 ;
236 [label=<蔬菜食用频率 ≤ 0.49
gini = 0.49
samples = 56
value = [0, 8, 1, 0, 0, 55, 18]
class = Overweight_Level_I>, fillcolor="#d28df0"] ;
228 -> 236 ;
237 [label=samples = 8
value = [0, 0, 0, 0, 0, 0, 10]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
236 -> 237 ;
238 [label=<每日水消耗量 ≤ 0.91
gini = 0.39
samples = 48
value = [0, 8, 1, 0, 0, 55, 8]
class = Overweight_Level_I>, fillcolor="#c66eec"] ;
236 -> 238 ;
239 [label=<体重 ≤ 0.29
gini = 0.25
samples = 38
value = [0, 5, 1, 0, 0, 50, 2]
class = Overweight_Level_I>, fillcolor="#bd57e9"] ;
238 -> 239 ;
240 [label=<每日水消耗量 ≤ 0.61
gini = 0.44
samples = 2
value = [0, 2, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#dbf29c"] ;
239 -> 240 ;
241 [label=samples = 1
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
240 -> 241 ;
242 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
240 -> 242 ;
243 [label=<高热量食物 ≤ 0.5
gini = 0.2
samples = 36
value = [0, 3, 1, 0, 0, 49, 2]
class = Overweight_Level_I>, fillcolor="#ba50e8"] ;
239 -> 243 ;
244 [label=samples = 1
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
243 -> 244 ;
245 [label=<蔬菜食用频率 ≤ 0.5
gini = 0.14
samples = 35
value = [0, 1, 1, 0, 0, 49, 2]
class = Overweight_Level_I>, fillcolor="#b749e7"] ;
243 -> 245 ;
246 [label=samples = 1
value = [0, 0, 1, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
245 -> 246 ;
247 [label=samples = 34
value = [0, 1, 0, 0, 0, 49, 2]
class = Overweight_Level_I>, fillcolor="#b645e7"] ;
245 -> 247 ;
248 [label=<身高 ≤ 0.58
gini = 0.64
samples = 10
value = [0, 3, 0, 0, 0, 5, 6]
class = Overweight_Level_II>, fillcolor="#fce9f2"] ;
238 -> 248 ;
249 [label=samples = 3
value = [0, 0, 0, 0, 0, 0, 5]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
248 -> 249 ;
250 [label=<身高 ≤ 0.77
gini = 0.57
samples = 7
value = [0, 3, 0, 0, 0, 5, 1]
class = Overweight_Level_I>, fillcolor="#e5bdf6"] ;
248 -> 250 ;
251 [label=<每日水消耗量 ≤ 0.99
gini = 0.32
samples = 5
value = [0, 0, 0, 0, 0, 4, 1]
class = Overweight_Level_I>, fillcolor="#c46aec"] ;
250 -> 251 ;
252 [label=samples = 2
value = [0, 0, 0, 0, 0, 1, 1]
class = Overweight_Level_I>, fillcolor="#ffffff"] ;
251 -> 252 ;
253 [label=samples = 3
value = [0, 0, 0, 0, 0, 3, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
251 -> 253 ;
254 [label=<蔬菜食用频率 ≤ 0.86
gini = 0.38
samples = 2
value = [0, 3, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#cfee7b"] ;
250 -> 254 ;
255 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
254 -> 255 ;
256 [label=samples = 1
value = [0, 3, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
254 -> 256 ;
257 [label=<体重 ≤ 0.37
gini = 0.38
samples = 110
value = [0, 3, 25, 0, 0, 11, 133]
class = Overweight_Level_II>, fillcolor="#ec6ea6"] ;
205 -> 257 ;
258 [label=<年龄 ≤ 0.76
gini = 0.23
samples = 77
value = [0, 3, 2, 0, 0, 11, 111]
class = Overweight_Level_II>, fillcolor="#e95497"] ;
257 -> 258 ;
259 [label=<身高 ≤ 0.65
gini = 0.13
samples = 74
value = [0, 3, 0, 0, 0, 5, 109]
class = Overweight_Level_II>, fillcolor="#e7478f"] ;
258 -> 259 ;
260 [label=<蔬菜食用频率 ≤ 0.5
gini = 0.07
samples = 71
value = [0, 1, 0, 0, 0, 3, 109]
class = Overweight_Level_II>, fillcolor="#e6408a"] ;
259 -> 260 ;
261 [label=<年龄 ≤ 0.25
gini = 0.5
samples = 4
value = [0, 0, 0, 0, 0, 2, 2]
class = Overweight_Level_I>, fillcolor="#ffffff"] ;
260 -> 261 ;
262 [label=samples = 2
value = [0, 0, 0, 0, 0, 0, 2]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
261 -> 262 ;
263 [label=samples = 2
value = [0, 0, 0, 0, 0, 2, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
261 -> 263 ;
264 [label=<年龄 ≤ 0.26
gini = 0.04
samples = 67
value = [0, 1, 0, 0, 0, 1, 107]
class = Overweight_Level_II>, fillcolor="#e53d88"] ;
260 -> 264 ;
265 [label=<身高 ≤ 0.55
gini = 0.14
samples = 21
value = [0, 1, 0, 0, 0, 1, 25]
class = Overweight_Level_II>, fillcolor="#e7488f"] ;
264 -> 265 ;
266 [label=samples = 19
value = [0, 0, 0, 0, 0, 0, 25]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
265 -> 266 ;
267 [label=<体重 ≤ 0.3
gini = 0.5
samples = 2
value = [0, 1, 0, 0, 0, 1, 0]
class = Normal_Weight>, fillcolor="#ffffff"] ;
265 -> 267 ;
268 [label=samples = 1
value = [0, 1, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
267 -> 268 ;
269 [label=samples = 1
value = [0, 0, 0, 0, 0, 1, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
267 -> 269 ;
270 [label=samples = 46
value = [0, 0, 0, 0, 0, 0, 82]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
264 -> 270 ;
271 [label=<蔬菜食用频率 ≤ 0.97
gini = 0.5
samples = 3
value = [0, 2, 0, 0, 0, 2, 0]
class = Normal_Weight>, fillcolor="#ffffff"] ;
259 -> 271 ;
272 [label=samples = 2
value = [0, 0, 0, 0, 0, 2, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
271 -> 272 ;
273 [label=samples = 1
value = [0, 2, 0, 0, 0, 0, 0]
class = Normal_Weight>, fillcolor="#b7e539"] ;
271 -> 273 ;
274 [label=<卡路里消耗 ≤ 0.5
gini = 0.56
samples = 3
value = [0, 0, 2, 0, 0, 6, 2]
class = Overweight_Level_I>, fillcolor="#d89cf2"] ;
258 -> 274 ;
275 [label=<体重 ≤ 0.34
gini = 0.5
samples = 2
value = [0, 0, 2, 0, 0, 0, 2]
class = Obesity_Type_I>, fillcolor="#ffffff"] ;
274 -> 275 ;
276 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 2]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
275 -> 276 ;
277 [label=samples = 1
value = [0, 0, 2, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
275 -> 277 ;
278 [label=samples = 1
value = [0, 0, 0, 0, 0, 6, 0]
class = Overweight_Level_I>, fillcolor="#b139e5"] ;
274 -> 278 ;
279 [label=<每日水消耗量 ≤ 0.8
gini = 0.5
samples = 33
value = [0, 0, 23, 0, 0, 0, 22]
class = Obesity_Type_I>, fillcolor="#f6fef7"] ;
257 -> 279 ;
280 [label=<身高 ≤ 0.54
gini = 0.42
samples = 20
value = [0, 0, 8, 0, 0, 0, 19]
class = Overweight_Level_II>, fillcolor="#f08cb9"] ;
279 -> 280 ;
281 [label=samples = 5
value = [0, 0, 8, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
280 -> 281 ;
282 [label=samples = 15
value = [0, 0, 0, 0, 0, 0, 19]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
280 -> 282 ;
283 [label=<体重 ≤ 0.45
gini = 0.28
samples = 13
value = [0, 0, 15, 0, 0, 0, 3]
class = Obesity_Type_I>, fillcolor="#61ea71"] ;
279 -> 283 ;
284 [label=<年龄 ≤ 0.4
gini = 0.22
samples = 11
value = [0, 0, 14, 0, 0, 0, 2]
class = Obesity_Type_I>, fillcolor="#55e966"] ;
283 -> 284 ;
285 [label=samples = 7
value = [0, 0, 10, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
284 -> 285 ;
286 [label=<体重 ≤ 0.43
gini = 0.44
samples = 4
value = [0, 0, 4, 0, 0, 0, 2]
class = Obesity_Type_I>, fillcolor="#9cf2a6"] ;
284 -> 286 ;
287 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 2]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
286 -> 287 ;
288 [label=samples = 3
value = [0, 0, 4, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
286 -> 288 ;
289 [label=<蔬菜食用频率 ≤ 0.51
gini = 0.5
samples = 2
value = [0, 0, 1, 0, 0, 0, 1]
class = Obesity_Type_I>, fillcolor="#ffffff"] ;
283 -> 289 ;
290 [label=samples = 1
value = [0, 0, 0, 0, 0, 0, 1]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
289 -> 290 ;
291 [label=samples = 1
value = [0, 0, 1, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
289 -> 291 ;
292 [label=<蔬菜食用频率 ≤ 1.0
gini = 0.61
samples = 457
value = [0, 0, 106, 293, 339, 0, 3]
class = Obesity_Type_III>, fillcolor="#ebeefc"] ;
0 -> 292 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
293 [label=<体重 ≤ 0.53
gini = 0.38
samples = 223
value = [0, 0, 90, 277, 0, 0, 3]
class = Obesity_Type_II>, fillcolor="#7beeec"] ;
292 -> 293 ;
294 [label=<每日水消耗量 ≤ 0.3
gini = 0.5
samples = 73
value = [0, 0, 73, 45, 0, 0, 3]
class = Obesity_Type_I>, fillcolor="#b6f5bd"] ;
293 -> 294 ;
295 [label=<酒精消耗量 ≤ 0.33
gini = 0.12
samples = 29
value = [0, 0, 3, 43, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#47e7e4"] ;
294 -> 295 ;
296 [label=samples = 27
value = [0, 0, 0, 43, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#39e5e2"] ;
295 -> 296 ;
297 [label=samples = 2
value = [0, 0, 3, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
295 -> 297 ;
298 [label=<体重 ≤ 0.47
gini = 0.13
samples = 44
value = [0, 0, 70, 2, 0, 0, 3]
class = Obesity_Type_I>, fillcolor="#47e759"] ;
294 -> 298 ;
299 [label=<酒精消耗量 ≤ 0.5
gini = 0.5
samples = 4
value = [0, 0, 3, 0, 0, 0, 3]
class = Obesity_Type_I>, fillcolor="#ffffff"] ;
298 -> 299 ;
300 [label=samples = 2
value = [0, 0, 3, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
299 -> 300 ;
301 [label=samples = 2
value = [0, 0, 0, 0, 0, 0, 3]
class = Overweight_Level_II>, fillcolor="#e53986"] ;
299 -> 301 ;
302 [label=<身高 ≤ 0.46
gini = 0.06
samples = 40
value = [0, 0, 67, 2, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#3fe652"] ;
298 -> 302 ;
303 [label=samples = 1
value = [0, 0, 0, 2, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#39e5e2"] ;
302 -> 303 ;
304 [label=samples = 39
value = [0, 0, 67, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
302 -> 304 ;
305 [label=<年龄 ≤ 0.15
gini = 0.13
samples = 150
value = [0, 0, 17, 232, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#48e7e4"] ;
293 -> 305 ;
306 [label=<身高 ≤ 0.71
gini = 0.11
samples = 11
value = [0, 0, 16, 1, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#45e758"] ;
305 -> 306 ;
307 [label=samples = 1
value = [0, 0, 0, 1, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#39e5e2"] ;
306 -> 307 ;
308 [label=samples = 10
value = [0, 0, 16, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
306 -> 308 ;
309 [label=<身高 ≤ 0.9
gini = 0.01
samples = 139
value = [0, 0, 1, 231, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#3ae5e2"] ;
305 -> 309 ;
310 [label=samples = 138
value = [0, 0, 0, 231, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#39e5e2"] ;
309 -> 310 ;
311 [label=samples = 1
value = [0, 0, 1, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
309 -> 311 ;
312 [label=<身高 ≤ 0.71
gini = 0.16
samples = 234
value = [0, 0, 16, 16, 339, 0, 0]
class = Obesity_Type_III>, fillcolor="#4b65e7"] ;
292 -> 312 ;
313 [label=<酒精消耗量 ≤ 0.5
gini = 0.08
samples = 217
value = [0, 0, 10, 5, 337, 0, 0]
class = Obesity_Type_III>, fillcolor="#425de6"] ;
312 -> 313 ;
314 [label=<身高 ≤ 0.59
gini = 0.32
samples = 3
value = [0, 0, 1, 4, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#6aece9"] ;
313 -> 314 ;
315 [label=samples = 2
value = [0, 0, 0, 4, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#39e5e2"] ;
314 -> 315 ;
316 [label=samples = 1
value = [0, 0, 1, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
314 -> 316 ;
317 [label=<每日水消耗量 ≤ 1.0
gini = 0.06
samples = 214
value = [0, 0, 9, 1, 337, 0, 0]
class = Obesity_Type_III>, fillcolor="#3f5be6"] ;
313 -> 317 ;
318 [label=<年龄 ≤ 0.26
gini = 0.05
samples = 213
value = [0, 0, 9, 0, 337, 0, 0]
class = Obesity_Type_III>, fillcolor="#3e5be6"] ;
317 -> 318 ;
319 [label=<身高 ≤ 0.55
gini = 0.04
samples = 211
value = [0, 0, 7, 0, 337, 0, 0]
class = Obesity_Type_III>, fillcolor="#3d5ae6"] ;
318 -> 319 ;
320 [label=samples = 154
value = [0, 0, 0, 0, 254, 0, 0]
class = Obesity_Type_III>, fillcolor="#3956e5"] ;
319 -> 320 ;
321 [label=<体重 ≤ 0.59
gini = 0.14
samples = 57
value = [0, 0, 7, 0, 83, 0, 0]
class = Obesity_Type_III>, fillcolor="#4a64e7"] ;
319 -> 321 ;
322 [label=samples = 4
value = [0, 0, 7, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
321 -> 322 ;
323 [label=samples = 53
value = [0, 0, 0, 0, 83, 0, 0]
class = Obesity_Type_III>, fillcolor="#3956e5"] ;
321 -> 323 ;
324 [label=samples = 2
value = [0, 0, 2, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
318 -> 324 ;
325 [label=samples = 1
value = [0, 0, 0, 1, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#39e5e2"] ;
317 -> 325 ;
326 [label=<体重 ≤ 0.55
gini = 0.55
samples = 17
value = [0, 0, 6, 11, 2, 0, 0]
class = Obesity_Type_II>, fillcolor="#b3f5f4"] ;
312 -> 326 ;
327 [label=samples = 5
value = [0, 0, 6, 0, 0, 0, 0]
class = Obesity_Type_I>, fillcolor="#39e54d"] ;
326 -> 327 ;
328 [label=<体重 ≤ 0.78
gini = 0.26
samples = 12
value = [0, 0, 0, 11, 2, 0, 0]
class = Obesity_Type_II>, fillcolor="#5deae7"] ;
326 -> 328 ;
329 [label=samples = 10
value = [0, 0, 0, 11, 0, 0, 0]
class = Obesity_Type_II>, fillcolor="#39e5e2"] ;
328 -> 329 ;
330 [label=samples = 2
value = [0, 0, 0, 0, 2, 0, 0]
class = Obesity_Type_III>, fillcolor="#3956e5"] ;
328 -> 330 ;
}