## 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,