def __init__(self, clf_kind, race_cnt=None, distance=None):
self.race_cnt = race_cnt
if clf_kind == 'randomforest':
self.clf = RandomForestClassifier(n_estimators=30, max_leaf_nodes=48, max_features=None, n_jobs=-1)
elif clf_kind == 'mlp':
self.clf = MLPClassifier(hidden_layer_sizes=(100, 90, 80, 70, 60, 50, 40, 30, 20, 10), solver='sgd', max_iter=5000, batch_size='auto')
elif clf_kind == 'mlp50':
self.clf = MLPClassifier(hidden_layer_sizes=(50), solver='sgd', max_iter=5000, batch_size='auto')
elif clf_kind == 'mlp70':
self.clf = MLPClassifier(hidden_layer_sizes=(70), solver='sgd', max_iter=5000, batch_size='auto')
elif clf_kind == 'mlp80':
self.clf = MLPClassifier(hidden_layer_sizes=(80), solver='sgd', max_iter=5000, batch_size='auto')
elif clf_kind == 'mlp90':
self.clf = MLPClassifier(hidden_layer_sizes=(90), solver='sgd', max_iter=5000, batch_size='auto')
elif clf_kind == 'mlp100':
self.clf = MLPClassifier(hidden_layer_sizes=(100), solver='sgd', max_iter=5000, batch_size='auto')
elif clf_kind == 'mlp100-50':
self.clf = MLPClassifier(hidden_layer_sizes=(100, 50), solver='sgd', max_iter=5000, batch_size='auto')
elif clf_kind == 'mlpgrid':
self.clf = GridSearchCV(MLPClassifier())
self.clf_kind = clf_kind
self.sc = StandardScaler()
self.distance = distance
self.ht_util = ht.HorseTableUtil()
args = sys.argv
self.argstr = ''
for num in range(1, len(args)):
self.argstr += args[num] + '_'
pkl_file_prefix = args[3]
order_limit = None
if len(args) > 4:
order_limit = int(args[4])
start = time.time()
t_util = train.TrainUtil(clf_kind)
clf_pkl = train.PKL_FILE_DIR + pkl_file_prefix + train.CLF_PKL_FILE_NAME
sc_pkl = train.PKL_FILE_DIR + pkl_file_prefix + train.SC_PKL_FILE_NAME
if os.path.isfile(clf_pkl) and os.path.isfile(sc_pkl):
t_util.clf = joblib.load(clf_pkl)
t_util.sc = joblib.load(sc_pkl)
else:
print('pklファイルが存在しません。')
sys.exit()
ht_util = ht.HorseTableUtil()
test_race_keys = ht_util.get_race_keys_debut_after_ymd(ymd)
if len(test_race_keys) == 0:
print('入力日に対象レースはありません。')
sys.exit()
t_util.predict_maiden(test_race_keys, order_limit)
t_util.print_return_maiden(test_race_keys)
elapsed_time = time.time() - start
print('elapsed_time:{0}'.format(elapsed_time) + '[sec]')
print(datetime.now().strftime("%Y/%m/%d %H:%M:%S"))
