def learning(self, path: str) -> None:
x = self._data.decisions.get_data()
y = self._data.decisions.get_answers()
Debug.learning(f'Start learning from {y.size} samples')
x_train, x_test, y_train, y_test = train_test_split(x,
y,
test_size=0.25)
mlp = MLPClassifier(hidden_layer_sizes=(200, 100, 100))
mlp.fit(x_train, y_train)
Debug.learning('train', mlp.score(x_train, y_train))
Debug.learning('test ', mlp.score(x_test, y_test))
if not exists('networks'):
mkdir('networks')
dump(mlp, open(f'networks/{path}', 'wb'))
def add_data_from_game(self, game: PokerGame) -> None:
Debug.learning('Start eject data from game', game.name)
for hand in game.hands:
self.add_data_from_hand(game, hand)
def add_data_set(self, games_path: str) -> None:
self._data.add_data_from_folder(games_path)
Debug.learning('data set contains', len(self._data.decisions),
'decisions with answers')