## Parameters
####################
N_ROUNDS = 30000
LR = 0.01
BOOSTING = "gbdt"
BAG_FREQ = 1
BAG_FRAC = 0.7
MIN_DATA_IN_LEAF = 50
SEED = 42
METRIC = "rmse"
L1 = 1e-2
L2 = 1e-2
MAX_DEPTH = 5
FEAT_FRAC = 0.9
update_tracking(MODEL_ID, "n_rounds", N_ROUNDS)
update_tracking(MODEL_ID, "lr", LR)
update_tracking(MODEL_ID, "boosting", BOOSTING)
update_tracking(MODEL_ID, "bag_freq", BAG_FREQ)
update_tracking(MODEL_ID, "bag_frac", BAG_FRAC)
update_tracking(MODEL_ID, "min_data_in_leaf", MIN_DATA_IN_LEAF)
update_tracking(MODEL_ID, "seed", SEED)
update_tracking(MODEL_ID, "metric", METRIC)
update_tracking(MODEL_ID, "lambda_l1", L1)
update_tracking(MODEL_ID, "lambda_l2", L2)
update_tracking(MODEL_ID, "max_depth", MAX_DEPTH)
update_tracking(MODEL_ID, "feature_fraction", FEAT_FRAC)
params = {"learning_rate": LR,
"boosting": BOOSTING,
logger = logging.getLogger("main")
logger.setLevel(logging.DEBUG)
sc = logging.StreamHandler()
logger.addHandler(sc)
fh = logging.FileHandler(f"./logs/model_logs/{MODEL_ID}.log")
logger.addHandler(fh)
logger.debug(f"./logs/model_logs/{MODEL_ID}.log")
####################
## Parameters
####################
KERNEL = "rbf"
C = 0.1
EPS = 0.1
update_tracking(MODEL_ID, "kernel", KERNEL)
update_tracking(MODEL_ID, "C", C)
update_tracking(MODEL_ID, "epsilon", EPS)
params = {"kernel": KERNEL, "C": C, "epsilon": EPS}
####################
## Load data
####################
# 変数名の英訳
train_cols_eng = [
"id", "rent", "location", "access", "layout", "age", "direction", "area",
"floor", "bath_toilet", "kitchen", "broad_com", "facility", "parking",
"environment", "structure", "contract_period"
]
test_cols_eng = [
logger.setLevel(logging.DEBUG)
sc = logging.StreamHandler()
logger.addHandler(sc)
fh = logging.FileHandler(f"./logs/model_logs/{MODEL_ID}.log")
logger.addHandler(fh)
logger.debug(f"./logs/model_logs/{MODEL_ID}.log")
####################
## Parameters
####################
ALPHA = 10
SEED = 42
update_tracking(MODEL_ID, "alpha", ALPHA)
update_tracking(MODEL_ID, "random_state", SEED)
params = {"alpha": ALPHA,
"random_state": SEED}
####################
## Load data
####################
# 変数名の英訳
train_cols_eng = ["id", "rent", "location", "access", "layout", "age", "direction", "area", "floor",
"bath_toilet", "kitchen", "broad_com", "facility", "parking", "environment", "structure",
"contract_period"]
test_cols_eng = ["id", "location", "access", "layout", "age", "direction", "area", "floor",
logger.addHandler(fh)
logger.debug(f"./logs/model_logs/{MODEL_ID}.log")
####################
## Parameters
####################
N_ROUNDS = 10000
LR = 0.01
BOOSTING = "gbdt"
BAG_FREQ = 1
BAG_FRAC = 0.7
MIN_DATA_IN_LEAF = 50
SEED = 42
METRIC = "rmse"
update_tracking(MODEL_ID, "n_rounds", N_ROUNDS)
update_tracking(MODEL_ID, "lr", LR)
update_tracking(MODEL_ID, "boosting", BOOSTING)
update_tracking(MODEL_ID, "bag_freq", BAG_FREQ)
update_tracking(MODEL_ID, "bag_frac", BAG_FRAC)
update_tracking(MODEL_ID, "min_data_in_leaf", MIN_DATA_IN_LEAF)
update_tracking(MODEL_ID, "seed", SEED)
update_tracking(MODEL_ID, "metric", METRIC)
params = {
"learning_rate": LR,
"boosting": BOOSTING,
"bagging_freq": BAG_FREQ,
"bagging_fraction": BAG_FRAC,
"min_data_in_leaf": MIN_DATA_IN_LEAF,
"bagging_seed": SEED,
