def __init__(self, weights):
game = hlt.Game()
game.ready("DecisionTreeBot")
m = model.HaliteModel(weights=weights)
self.m = m
self.game = game
def __init__(self, weights):
# Get the initial game state
game = hlt.Game()
game.ready(os.path.basename(weights))
# During init phase: initialize the model and compile it
my_model = model.HaliteModel(weights=weights)
self.my_model = my_model
self.game = game
def __init__(self, weights):
# Get the initial game state
game = hlt.Game()
logging.info("Successfully created bot! My Player ID is {}.".format(game.my_id))
game.ready("SVM-" + os.path.basename(weights))
# During init phase: initialize the model and compile it
my_model = model.HaliteModel(weights=weights)
self.my_model = my_model
self.game = game
def main():
bot = model.HaliteModel(weights="out/dt.svc")
dot_data = tree.export_graphviz(bot.model,
out_file="out/dt.dot",
feature_names=FEATURE_NAMES,
class_names=TARGET_NAMES,
filled=True,
rounded=True,
special_characters=True)
print(
"Dot file generated at out/dt.dot. Please run util/render.sh to generate a png file."
)
#!/usr/bin/env python3
import model
#m = model.HaliteModel()
#m.train_on_files('replays', 'aggressive')
#m.save(file_name='aggressive.svc')
m = model.HaliteModel()
m.train_on_files('replays', 'aggressive')
m.save(file_name='aggressive.svc')
m = model.HaliteModel()
m.train_on_files('replays', 'passive')
m.save(file_name='passive.svc')
def main():
m = model.HaliteModel()
m.train_on_folder("./training")
m.save(file_name="out/dt.svc")
print("Training complete. SVC file at out/dt.svc")
print("call ./run_game.sh to test bot")