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This commit is contained in:
Miron 2021-05-23 22:05:49 +02:00
parent 351af34703
commit 9a74d214b5
8 changed files with 244 additions and 219 deletions
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src/__pycache__/tree.cpython-38.pyc Normal file
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91
src/main.py
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@ -2,8 +2,9 @@ import pygame
import random
import time
from src.a_star import a_star_search, WAREHOUSE_MAP, St
from src.bfs import breadth_first_search
from src.a_star import a_star_search, WAREHOUSE_MAP
from src.training_data.scripts.gen_data_id3 import generate_size, generate_weight, generate_price, generate_flammability, generate_explosiveness
from src.tree import predict_result, load_tree_from_structure
pygame.init()
@ -12,6 +13,7 @@ HEIGHT = 675
size = 75
QTY_OF_PACKAGES = 8
RECT_SIZE = 9
data_tree = load_tree_from_structure('tree/tree_model')
IMAGE = pygame.image.load('img/wozek2.png')
BACKGROUND = pygame.transform.scale(pygame.image.load('img/background.png'), (WIDTH, HEIGHT))
@ -39,20 +41,46 @@ def create_positions():
def generate_package(a, b):
rand_y = random.randint(1, 4)
rand_x = random.randint(10, 150)
name_list = ['Grocery', 'Explosive', 'Electronic', 'Builders']
image_list = ['img/package_grocery.png', 'img/package_explosive.png', 'img/package.png', 'img/package_builders.png']
p1 = Package((a, b), rand_x, name_list[rand_y - 1], image_list[rand_y - 1])
name_list = ['Grocery', 'Builders', 'Electronic', 'Explosive']
image_list = ['img/package_grocery.png', 'img/package_builders.png', 'img/package.png', 'img/package_explosive.png']
rand_type = random.randint(1, 4)
#rand_weight = generate_weight()
rand_weight = random.randint(1, 10)
#rand_size = generate_size()
rand_size = random.randint(1, 10)
rand_flammability = generate_flammability(name_list[rand_type - 1])
rand_explosiveness = generate_explosiveness(name_list[rand_type - 1])
#rand_price = generate_price()
rand_price = random.randint(1, 10)
p1 = Package((a, b), rand_weight, rand_type, rand_size, rand_flammability, rand_explosiveness, rand_price,
image_list[rand_type - 1])
return p1
# class Package:
# def __init__(self, pos, content, content_size, pack_image):
# self.pos = pos
# self.content = content
# self.content_size = content_size
# self.image = pygame.transform.scale(pygame.image.load(pack_image), (50, 50))
# self.rect = self.image.get_rect(center=pos)
# self.is_package_up = False
class Package:
def __init__(self, pos, content, content_size, pack_image):
def __init__(self, pos, package_weight, package_type, package_size, flammability, explosiveness, price, image):
self.pos = pos
self.content = content
self.content_size = content_size
self.image = pygame.transform.scale(pygame.image.load(pack_image), (50, 50))
self.package_weight = package_weight
self.package_type = package_type
name_list = ['Grocery', 'Builders', 'Electronic', 'Explosive']
self.package_type_name = name_list[package_type - 1]
self.package_size = package_size
self.flammability = flammability
self.explosiveness = explosiveness
self.price = price
self.image = pygame.transform.scale(pygame.image.load(image), (50, 50))
self.is_accepted = predict_result(data_tree, self.package_weight, self.package_type, self.package_size, self.flammability, self.explosiveness, self.price)[0]
#self.is_accepted = 0
self.rect = self.image.get_rect(center=pos)
self.is_package_up = False
@ -157,6 +185,10 @@ class Agent:
package.is_package_up = False
elif package.pos == agent.pos:
package.is_package_up = True
print("TYP: {}, WAGA: {}, ROZMIAR: {}, LATWOPALNOSC: {}, WYBUCHOWOSC: {}, CENA: {}, CZY PRZYJETA: {}"
.format(package.package_type_name, package.package_weight, package.package_size,
package.flammability,
package.explosiveness, package.price, package.is_accepted))
def goal_test(self, state):
if state == self.goal:
@ -167,10 +199,8 @@ class Agent:
board = pygame.Surface((WIDTH, HEIGHT), pygame.SRCALPHA) # transparently surface
create_positions()
# Rysowanie lini
for x in range(9):
for y in range(9):
@ -187,27 +217,25 @@ Shelf_list = [
Shelf((5, 8), 'Electronic', 5), Shelf((6, 8), 'Electronic', 5), Shelf((7, 8), 'Electronic', 5),
Shelf((8, 8), 'Electronic', 5)]
coord_goals = [(8, 0), (0, 0), (5, 8), (0, 0), (8, 0), (0, 0), (8, 8), (0, 0),
(5, 6), (0, 0), (6, 6), (0, 0), (7, 6), (0, 0), (8, 6), (0, 8)]
coord_goals = [(0, 0)]
free_shelf = [(5, 8), (6, 8), (7, 8), (8, 8), (5, 6), (6, 6), (7, 6), (8, 6)]
screen = pygame.display.set_mode([WIDTH, HEIGHT])
Package_list = [
generate_package(40, 40)
Package((40, 40), 3, 4, 6, 3, 3, 6, 'img/package_explosive.png')
]
agent.path = a_star_search((agent.pos_coord[1], agent.pos_coord[0]), coord_goals.pop(0), agent.agent_direction)
#print(a_star_search((6, 8), (0, 0), "down"))
agent.path = a_star_search((agent.pos_coord[1], agent.pos_coord[0]), (0, 0), agent.agent_direction)
# Pętla służąca do tworzenia plam oleju na podstawie mapy magazynu
Stain_list = []
for index_x in range(9):
for index_y in range(9):
if WAREHOUSE_MAP[index_x][index_y] == St:
if WAREHOUSE_MAP[index_x][index_y] == 10:
Stain_list.append(Stain((index_y, index_x)))
running = True
while running:
@ -226,9 +254,14 @@ while running:
for package in Package_list:
if package.pos == (40, 40):
is_dock_empty = False
elif package.pos == get_pix_from_position[(8, 0)] and not package.is_package_up:
print("Paczka wyrzucona")
Package_list.remove(package)
is_dock_empty = False
elif get_position_from_pix(package.pos) in free_shelf:
Package_list.remove(package)
is_dock_empty = False
if is_dock_empty:
Package_list.append(generate_package(40, 40))
@ -239,14 +272,22 @@ while running:
agent.move_bfs()
else:
agent.lift_package_bfs()
if coord_goals:
if agent.pos_coord == (0, 0):
if Package_list[-1].is_accepted == 1:
coord_goals.append(free_shelf[random.randint(0, 7)])
coord_goals.append((0, 0))
else:
coord_goals.append((8, 0))
coord_goals.append((0, 0))
agent.goal = coord_goals.pop(0)
agent.goal_achieved = False
#agent.path = breadth_first_search(agent.pos_coord, agent.goal, agent.agent_direction)
agent.path = a_star_search((agent.pos_coord[1], agent.pos_coord[0]), (agent.goal[1], agent.goal[0]), agent.agent_direction)
agent.path = a_star_search((agent.pos_coord[1], agent.pos_coord[0]), (agent.goal[1], agent.goal[0]),
agent.agent_direction)
for package in Package_list:
if package.is_package_up:
@ -266,7 +307,7 @@ while running:
for package in Package_list:
screen.blit(package.image, package.rect)
time.sleep(0.15)
time.sleep(0.05)
pygame.display.update()

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src/training_data/scripts/data/training_list_id3.csv
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@ -1,3 +1,5 @@
3,4,6,2,3,8,0
3,4,6,2,3,8,1
10,2,2,0,0,4,0
1,1,4,0,0,5,1
5,1,10,0,0,10,0
@ -65,7 +67,7 @@
2,3,8,3,0,1,1
9,4,2,5,4,5,0
8,3,5,0,0,3,1
9,4,3,3,4,1,1
9,4,3,3,4,1,0
7,4,6,3,3,2,1
1,2,2,4,0,5,0
3,1,3,0,0,10,0
@ -89,7 +91,7 @@
10,3,5,0,0,2,1
4,2,7,5,0,2,0
4,4,10,4,2,9,0
9,3,6,0,0,5,1
9,3,6,0,0,5,0
4,2,1,0,0,3,1
2,2,1,1,2,8,1
10,4,4,4,4,4,0
@ -101,7 +103,7 @@
2,1,2,0,0,1,1
2,3,3,0,0,2,1
4,1,7,0,0,3,1
9,3,7,0,0,1,1
9,3,7,0,0,1,0
3,3,6,0,0,4,1
8,4,4,3,5,2,0
5,3,3,0,0,3,1
@ -115,7 +117,7 @@
3,1,4,0,0,1,1
1,3,3,0,0,4,1
6,1,6,0,0,2,1
10,1,2,0,0,5,1
10,1,2,0,0,5,0
7,1,3,0,0,4,1
7,3,4,0,0,8,1
1,3,7,0,0,2,1
@ -143,19 +145,19 @@
4,4,7,3,5,4,0
5,2,5,0,0,3,1
1,3,7,0,0,4,1
10,3,6,1,0,7,1
10,3,6,1,0,7,0
3,2,5,5,0,8,0
1,1,1,0,0,1,1
3,3,6,0,0,3,1
2,3,3,0,0,5,1
4,2,3,0,1,10,1
4,2,3,0,1,10,0
4,2,2,0,0,5,1
3,3,7,0,0,5,1
3,2,6,5,0,2,0
9,2,1,5,1,3,0
7,1,8,0,0,1,0
2,1,9,0,0,3,0
6,3,1,4,0,9,1
2,1,9,0,0,3,1
6,3,1,4,0,9,0
4,3,5,0,0,4,1
5,4,6,3,3,5,1
1,2,10,2,0,3,0
@ -191,7 +193,7 @@
3,2,2,3,2,2,1
2,1,7,0,0,5,1
1,2,3,0,2,4,1
9,2,5,0,0,2,0
9,2,5,0,0,2,1
4,3,8,5,0,5,0
2,2,6,4,0,1,1
3,3,4,0,2,3,1

1 10 3 4 2 6 2 0 3 8 0 0
1 3 4 6 2 3 8 0
2 3 4 6 2 3 8 1
3 10 10 4 2 2 2 2 0 0 0 4 0 0
4 1 1 5 1 4 4 1 0 0 0 5 1 0 1
5 5 5 10 1 10 10 1 0 0 0 10 0 0
67 2 2 1 3 8 8 3 0 0 1 1 3 1
68 9 9 5 4 2 2 4 5 4 4 5 0 5 0
69 8 8 3 5 5 3 0 0 0 3 1 0 1
70 9 9 1 4 3 3 4 3 4 4 1 1 3 0
71 7 7 2 4 6 6 4 3 3 3 2 1 3 1
72 1 1 5 2 2 2 2 4 0 0 5 0 4 0
73 3 3 10 1 3 3 1 0 0 0 10 0 0
91 10 10 2 3 5 5 3 0 0 0 2 1 0 1
92 4 4 2 7 7 2 5 0 0 2 0 5 0
93 4 4 9 4 10 10 4 2 2 9 0 4 0
94 9 9 5 3 6 6 3 0 0 0 5 1 0
95 4 4 3 2 1 1 2 0 0 0 3 1 0 1
96 2 2 8 2 1 1 2 1 2 2 8 1 1
97 10 10 4 4 4 4 4 4 4 0 4 0
103 2 2 1 2 2 1 0 0 0 1 1 0 1
104 2 2 2 3 3 3 3 0 0 0 2 1 0 1
105 4 4 3 1 7 7 1 0 0 0 3 1 0 1
106 9 9 1 3 7 7 3 0 0 0 1 1 0
107 3 3 4 3 6 6 3 0 0 0 4 1 0 1
108 8 8 2 4 4 4 4 3 5 5 2 0 3 0
109 5 5 3 3 3 3 0 0 0 3 1 0 1
117 3 3 1 4 4 1 0 0 0 1 1 0 1
118 1 1 4 3 3 3 3 0 0 0 4 1 0 1
119 6 6 2 1 6 6 1 0 0 0 2 1 0 1
120 10 10 5 1 2 2 1 0 0 0 5 1 0
121 7 7 4 1 3 3 1 0 0 0 4 1 0 1
122 7 7 8 3 4 4 3 0 0 0 8 1 0 1
123 1 1 2 3 7 7 3 0 0 0 2 1 0 1
145 4 4 4 7 7 4 3 5 5 4 0 3 0
146 5 5 3 2 5 5 2 0 0 0 3 1 0 1
147 1 1 4 3 7 7 3 0 0 0 4 1 0 1
148 10 10 7 3 6 6 3 1 0 0 7 1 1 0
149 3 3 8 2 5 5 2 5 0 0 8 0 5 0
150 1 1 1 1 1 1 0 0 0 1 1 0 1
151 3 3 3 6 6 3 0 0 0 3 1 0 1
152 2 2 5 3 3 3 3 0 0 0 5 1 0 1
153 4 4 10 2 3 3 2 0 1 1 10 1 0
154 4 4 5 2 2 2 2 0 0 0 5 1 0 1
155 3 3 5 3 7 7 3 0 0 0 5 1 0 1
156 3 3 2 6 6 2 5 0 0 2 0 5 0
157 9 9 3 2 1 1 2 5 1 1 3 0 5 0
158 7 7 1 8 8 1 0 0 0 1 0 0
159 2 2 3 1 9 9 1 0 0 0 3 0 0 1
160 6 6 9 3 1 1 3 4 0 0 9 1 4 0
161 4 4 4 3 5 5 3 0 0 0 4 1 0 1
162 5 5 5 4 6 6 4 3 3 3 5 1 3 1
163 1 1 3 2 10 10 2 0 0 3 0 2 0
193 3 3 2 2 2 2 3 2 2 2 1 3 1
194 2 2 5 1 7 7 1 0 0 0 5 1 0 1
195 1 1 4 2 3 3 2 0 2 2 4 1 0 1
196 9 9 2 5 5 2 0 0 0 2 0 0 1
197 4 4 5 3 8 8 3 5 0 0 5 0 5 0
198 2 2 1 2 6 6 2 4 0 0 1 1 4 1
199 3 3 3 4 4 3 0 2 2 3 1 0 1

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src/tree.py
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@ -4,8 +4,8 @@ import pandas
from sklearn import tree
from sklearn.tree import DecisionTreeClassifier
columns = ["weight", "type", "size", "inflammability", "explosiveness", "prize", "allowed_in"]
attributes = ["weight", "type", "size", "inflammability", "explosiveness", "prize"]
columns = ["weight", "type", "size", "inflammability", "explosiveness", "price", "allowed_in"]
attributes = ["weight", "type", "size", "inflammability", "explosiveness", "price"]
decisions = ["allowed_in"]
@ -21,8 +21,8 @@ def learning_tree():
return decision_tree
def making_decision(decision_tree, weight, type, size, inflammability, explosiveness, prize):
decision = decision_tree.predict([[weight, type, size, inflammability, explosiveness, prize]])
def predict_result(decision_tree, weight, type, size, inflammability, explosiveness, price):
decision = decision_tree.predict([[weight, type, size, inflammability, explosiveness, price]])
return decision
@ -50,3 +50,9 @@ def save_tree_to_structure(decision_tree):
def load_tree_from_structure(file):
return joblib.load(file)
if __name__ == "__main__":
tree_data = learning_tree()
save_all(tree_data)

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src/tree/tree_in_txt.txt
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@ -1,6 +1,6 @@
|--- feature_3 <= 2.50
| |--- feature_5 <= 9.50
| | |--- feature_0 <= 8.50
|--- feature_0 <= 8.50
| |--- feature_5 <= 8.50
| | |--- feature_3 <= 1.50
| | | |--- feature_2 <= 7.50
| | | | |--- feature_5 <= 7.50
| | | | | |--- feature_2 <= 2.50
@ -13,130 +13,106 @@
| | | | | | | | |--- feature_5 <= 3.00
| | | | | | | | | |--- class: 1
| | | | | | | | |--- feature_5 > 3.00
| | | | | | | | | |--- feature_3 <= 1.00
| | | | | | | | | | |--- class: 0
| | | | | | | | | |--- feature_3 > 1.00
| | | | | | | | | | |--- class: 1
| | | | | | | | | |--- class: 0
| | | | | |--- feature_2 > 2.50
| | | | | | |--- class: 1
| | | | |--- feature_5 > 7.50
| | | | | |--- feature_3 <= 0.50
| | | | | | |--- feature_2 <= 2.50
| | | | | | | |--- class: 0
| | | | | | |--- feature_2 > 2.50
| | | | | | | |--- feature_0 <= 3.50
| | | | | | | | |--- feature_2 <= 5.50
| | | | | | | | | |--- class: 0
| | | | | | | | |--- feature_2 > 5.50
| | | | | | | | | |--- class: 1
| | | | | | | |--- feature_0 > 3.50
| | | | | | | | |--- class: 1
| | | | | |--- feature_3 > 0.50
| | | | | |--- feature_1 <= 2.50
| | | | | | |--- class: 1
| | | | | |--- feature_1 > 2.50
| | | | | | |--- feature_0 <= 4.50
| | | | | | | |--- class: 0
| | | | | | |--- feature_0 > 4.50
| | | | | | | |--- class: 1
| | | |--- feature_2 > 7.50
| | | | |--- feature_1 <= 2.50
| | | | | |--- feature_2 <= 9.50
| | | | | | |--- class: 0
| | | | | |--- feature_2 > 9.50
| | | | | | |--- feature_5 <= 2.00
| | | | |--- feature_0 <= 5.00
| | | | | |--- feature_2 <= 8.50
| | | | | | |--- class: 1
| | | | | |--- feature_2 > 8.50
| | | | | | |--- feature_2 <= 9.50
| | | | | | | |--- feature_1 <= 1.50
| | | | | | | | |--- feature_5 <= 3.50
| | | | | | | | | |--- class: 1
| | | | | | | | |--- feature_5 > 3.50
| | | | | | | | | |--- class: 0
| | | | | | | |--- feature_1 > 1.50
| | | | | | | | |--- class: 0
| | | | | | |--- feature_2 > 9.50
| | | | | | | |--- class: 1
| | | | | | |--- feature_5 > 2.00
| | | | | | | |--- class: 0
| | | | |--- feature_1 > 2.50
| | | | | |--- feature_2 <= 9.00
| | | | | | |--- class: 1
| | | | | |--- feature_2 > 9.00
| | | | | | |--- class: 0
| | |--- feature_0 > 8.50
| | | |--- feature_5 <= 1.50
| | | | |--- class: 1
| | | |--- feature_5 > 1.50
| | | | |--- feature_5 <= 6.50
| | | | | |--- feature_2 <= 4.50
| | | | | | |--- feature_1 <= 1.50
| | | | | | | |--- feature_0 <= 9.50
| | | | | | | | |--- class: 0
| | | | | | | |--- feature_0 > 9.50
| | | | | | | | |--- class: 1
| | | | | | |--- feature_1 > 1.50
| | | | | | | |--- class: 0
| | | | | |--- feature_2 > 4.50
| | | | | | |--- feature_1 <= 2.50
| | | | | | | |--- class: 0
| | | | | | |--- feature_1 > 2.50
| | | | | | | |--- feature_4 <= 1.00
| | | | | | | | |--- class: 1
| | | | | | | |--- feature_4 > 1.00
| | | | | | | | |--- class: 0
| | | | |--- feature_5 > 6.50
| | | | | |--- class: 1
| |--- feature_5 > 9.50
| | |--- feature_4 <= 0.50
| | | |--- class: 0
| | |--- feature_4 > 0.50
| | | |--- class: 1
|--- feature_3 > 2.50
| |--- feature_3 <= 4.50
| | |--- feature_2 <= 8.50
| | | |--- feature_0 <= 1.50
| | | | |--- feature_1 <= 3.50
| | | | | |--- feature_5 <= 3.00
| | | | | | |--- class: 1
| | | | | |--- feature_5 > 3.00
| | | | | | |--- class: 0
| | | | |--- feature_1 > 3.50
| | | | |--- feature_0 > 5.00
| | | | | |--- class: 0
| | | |--- feature_0 > 1.50
| | | | |--- feature_0 <= 6.50
| | | | | |--- feature_0 <= 4.50
| | | | | | |--- feature_5 <= 7.00
| | | | | | | |--- feature_0 <= 2.50
| | |--- feature_3 > 1.50
| | | |--- feature_4 <= 3.50
| | | | |--- feature_2 <= 9.00
| | | | | |--- feature_3 <= 4.50
| | | | | | |--- feature_1 <= 3.50
| | | | | | | |--- feature_3 <= 3.50
| | | | | | | | |--- class: 1
| | | | | | | |--- feature_0 > 2.50
| | | | | | | | |--- feature_2 <= 6.00
| | | | | | | | | |--- feature_4 <= 2.50
| | | | | | | | | | |--- feature_1 <= 3.00
| | | | | | | | | | | |--- class: 1
| | | | | | | | | | |--- feature_1 > 3.00
| | | | | | | |--- feature_3 > 3.50
| | | | | | | | |--- feature_5 <= 4.00
| | | | | | | | | |--- class: 1
| | | | | | | | |--- feature_5 > 4.00
| | | | | | | | | |--- class: 0
| | | | | | |--- feature_1 > 3.50
| | | | | | | |--- feature_3 <= 3.50
| | | | | | | | |--- feature_2 <= 3.50
| | | | | | | | | |--- class: 0
| | | | | | | | |--- feature_2 > 3.50
| | | | | | | | | |--- feature_0 <= 4.50
| | | | | | | | | | |--- feature_5 <= 2.50
| | | | | | | | | | | |--- class: 0
| | | | | | | | | |--- feature_4 > 2.50
| | | | | | | | | | |--- feature_5 > 2.50
| | | | | | | | | | | |--- truncated branch of depth 3
| | | | | | | | | |--- feature_0 > 4.50
| | | | | | | | | | |--- class: 1
| | | | | | | | |--- feature_2 > 6.00
| | | | | | | | | |--- feature_3 <= 3.50
| | | | | | | | | | |--- class: 0
| | | | | | | | | |--- feature_3 > 3.50
| | | | | | | | | | |--- feature_0 <= 3.50
| | | | | | | | | | | |--- class: 0
| | | | | | | | | | |--- feature_0 > 3.50
| | | | | | | | | | | |--- class: 1
| | | | | | |--- feature_5 > 7.00
| | | | | | | |--- class: 0
| | | | | |--- feature_0 > 4.50
| | | | | | |--- class: 1
| | | | |--- feature_0 > 6.50
| | | | | |--- feature_5 <= 2.50
| | | | | | |--- feature_4 <= 4.50
| | | | | | | |--- feature_3 > 3.50
| | | | | | | | |--- feature_0 <= 2.00
| | | | | | | | | |--- class: 0
| | | | | | | | |--- feature_0 > 2.00
| | | | | | | | | |--- class: 1
| | | | | |--- feature_3 > 4.50
| | | | | | |--- feature_2 <= 2.50
| | | | | | | |--- class: 1
| | | | | | |--- feature_4 > 4.50
| | | | | | | |--- class: 0
| | | | | |--- feature_5 > 2.50
| | | | | | |--- class: 0
| | |--- feature_2 > 8.50
| | | |--- class: 0
| |--- feature_3 > 4.50
| | |--- feature_0 <= 2.50
| | | |--- feature_2 <= 2.50
| | | | |--- class: 1
| | | |--- feature_2 > 2.50
| | | | |--- class: 0
| | |--- feature_0 > 2.50
| | | |--- feature_4 <= 0.50
| | | | |--- feature_0 <= 5.50
| | | | | | |--- feature_2 > 2.50
| | | | | | | |--- feature_0 <= 5.50
| | | | | | | | |--- class: 0
| | | | | | | |--- feature_0 > 5.50
| | | | | | | | |--- class: 1
| | | | |--- feature_2 > 9.00
| | | | | |--- class: 0
| | | | |--- feature_0 > 5.50
| | | | | |--- feature_0 <= 8.00
| | | |--- feature_4 > 3.50
| | | | |--- feature_3 <= 3.50
| | | | | |--- feature_4 <= 4.50
| | | | | | |--- class: 1
| | | | | |--- feature_0 > 8.00
| | | | | | |--- class: 0
| | | |--- feature_4 > 0.50
| | | | | |--- feature_4 > 4.50
| | | | | | |--- feature_2 <= 3.50
| | | | | | | |--- feature_2 <= 1.50
| | | | | | | | |--- class: 0
| | | | | | | |--- feature_2 > 1.50
| | | | | | | | |--- class: 1
| | | | | | |--- feature_2 > 3.50
| | | | | | | |--- class: 0
| | | | |--- feature_3 > 3.50
| | | | | |--- class: 0
| |--- feature_5 > 8.50
| | |--- feature_0 <= 1.50
| | | |--- class: 1
| | |--- feature_0 > 1.50
| | | |--- feature_2 <= 1.50
| | | | |--- feature_0 <= 3.00
| | | | | |--- class: 1
| | | | |--- feature_0 > 3.00
| | | | | |--- class: 0
| | | |--- feature_2 > 1.50
| | | | |--- class: 0
|--- feature_0 > 8.50
| |--- feature_5 <= 2.50
| | |--- feature_1 <= 2.50
| | | |--- class: 1
| | |--- feature_1 > 2.50
| | | |--- feature_0 <= 9.50
| | | | |--- class: 0
| | | |--- feature_0 > 9.50
| | | | |--- class: 1
| |--- feature_5 > 2.50
| | |--- class: 0

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src/tree/tree_model
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