lgbm, hyperparameters

lgbm_parameters = {
    'metric': 'rmse', 
    'n_jobs': -1,
    'n_estimators': 50000,
    'reg_alpha': 10.924491968127692,
    'reg_lambda': 17.396730654687218,
    'colsample_bytree': 0.21497646795452627,
    'subsample': 0.7582562557431147,
    'learning_rate': 0.009985133666265425,
    'max_depth': 18,
    'num_leaves': 63,
    'min_child_samples': 27,
    'max_bin': 523,
    'cat_l2': 0.025083670064082797
}

lgbm_parameters = {
    'metric': 'rmse', 
    'n_jobs': -1,
    'n_estimators': 10000,
    'reg_alpha': 10.924491968127692,
    'reg_lambda': 17.396730654687218,
    'colsample_bytree': 0.21497646795452627,
    'subsample': 0.7582562557431147,
    'learning_rate': 0.01,
    'max_depth': 12,
    'num_leaves': 32,
    'min_child_samples': 16,
    'max_bin': 256,
    'cat_l2': 0.025083670064082797
}
early_sr=64

params_lgb = {
    "task": "train",
    "boosting_type": "gbdt",
    "objective": "regression",
    "metric": "rmse",
    "learning_rate": 0.007899156646724397,
    "num_leaves": 77,
    "max_depth": 77,
    "feature_fraction": 0.2256038826485174,
    "bagging_fraction": 0.7705303688019942,
    "min_child_samples": 290,
    "reg_alpha": 9.562925363678952,
    "reg_lambda": 9.355810045480153,
    "max_bin": 772,
    "min_data_per_group": 177,
    "bagging_freq": 1,
    "cat_smooth": 96,
    "cat_l2": 17,
    "verbosity": -1,
    "bagging_seed": SEED,
    "feature_fraction_seed": SEED,
    "seed": SEED
}

lgbmparams = {'random_state': SEED,
          'metric': 'rmse',
          'n_estimators': N_ESTIMATORS,
          'n_jobs': -1,
          'cat_feature': [x for x in range(len(cat_features))],
          'bagging_seed': SEED,
          'feature_fraction_seed': SEED,
          'learning_rate': 0.003899156646724397,
          'max_depth': 99,
          'num_leaves': 63,
          'reg_alpha': 9.562925363678952,
          'reg_lambda': 9.355810045480153,
          'colsample_bytree': 0.2256038826485174,
          'min_child_samples': 290,
          'subsample_freq': 1,
          'subsample': 0.8805303688019942,
          'max_bin': 882,
          'min_data_per_group': 127,
          'cat_smooth': 96,
          'cat_l2': 19
          }

{min_child_weight: 16.66678543930681, 
min_data_in_leaf: 90, 
num_leaves: 3, 
subsample: 0.9379919580619296, 
colsample_bytree: 0.9685054958137231, 
scale_pos_weight: 1.3855266087693392}

Source: Various Kaggle notebooks.

LGBM Hyperparameters