diff --git "a/models/modelo_cluster_2.txt" "b/models/modelo_cluster_2.txt"
new file mode 100644--- /dev/null
+++ "b/models/modelo_cluster_2.txt"
@@ -0,0 +1,20849 @@
+tree
+version=v4
+num_class=1
+num_tree_per_iteration=1
+label_index=0
+max_feature_idx=27
+objective=regression
+feature_names=precio_total_lag_1 precio_total_lag_2 precio_total_lag_3 precio_total_lag_4 precio_total_lag_5 precio_total_lag_6 precio_total_lag_7 precio_total_lag_8 precio_total_lag_9 precio_total_lag_10 precio_total_lag_11 precio_total_lag_12 precio_total_lag_13 precio_total_lag_14 precio_total_lag_15 precio_total_lag_16 precio_total_lag_17 precio_total_lag_18 precio_total_lag_19 precio_total_lag_20 precio_total_lag_21 precio_total_lag_22 precio_total_lag_23 precio_total_lag_24 mes marca_id_encoded año cluster_id
+feature_infos=[0:2440] [0:2440] [0:1214.25] [0:1214.25] [0:1214.25] [0:1214.25] [0:1214.25] [0:1214.25] [0:1214.25] [0:1214.25] [0:1214.25] [0:1214.25] [0:1214.25] [0:1214.25] [0:1214.25] [0:1214.25] [0:1214.25] [0:1173.5999999999999] [0:1062.5999999999999] [0:1062.5999999999999] [0:1062.5999999999999] [0:1062.5999999999999] [0:1062.5999999999999] [0:393.12] -1:0:1:2:3:4:5:6:7:8:9:10:11 -1:10:4:117:5:9:52:93:12:100:20:121:27:59:120:56:54:15:32:37:64:25:68:0:63:2:40:57:66:97:18:38:24:76:95:19:36:53:77:88:7:51:58:99:87:3:16:26:30:31:96:109:1:13:17:28:29:35:41:42:44:47:48:69:73:74:82:84:106:8:14:21:23:34:60:79:86:89:92:94:83:85:108:105:118:6:11:22:33:39:43:45:46:49:50:55:61:62:65:67:70:71:72:75:78:80:90:91:98:110:119:81:101:102:103:104:107:111:112:113:114:116 [2022:2023] none
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+año=1671
+precio_total_lag_1=1133
+precio_total_lag_5=1088
+mes=934
+precio_total_lag_4=824
+precio_total_lag_9=732
+precio_total_lag_2=724
+precio_total_lag_7=676
+precio_total_lag_6=669
+precio_total_lag_11=645
+precio_total_lag_3=622
+precio_total_lag_8=567
+precio_total_lag_16=362
+precio_total_lag_10=246
+precio_total_lag_12=219
+precio_total_lag_14=214
+precio_total_lag_15=136
+precio_total_lag_13=108
+precio_total_lag_18=52
+precio_total_lag_17=28
+precio_total_lag_20=22
+precio_total_lag_21=20
+precio_total_lag_19=18
+
+parameters:
+[boosting: gbdt]
+[objective: regression]
+[metric: rmse]
+[tree_learner: serial]
+[device_type: cpu]
+[data_sample_strategy: bagging]
+[data: ]
+[valid: ]
+[num_iterations: 1000]
+[learning_rate: 0.01]
+[num_leaves: 64]
+[num_threads: 0]
+[seed: 0]
+[deterministic: 0]
+[force_col_wise: 0]
+[force_row_wise: 0]
+[histogram_pool_size: -1]
+[max_depth: 7]
+[min_data_in_leaf: 20]
+[min_sum_hessian_in_leaf: 0.001]
+[bagging_fraction: 0.8]
+[pos_bagging_fraction: 1]
+[neg_bagging_fraction: 1]
+[bagging_freq: 5]
+[bagging_seed: 3]
+[feature_fraction: 0.8]
+[feature_fraction_bynode: 1]
+[feature_fraction_seed: 2]
+[extra_trees: 0]
+[extra_seed: 6]
+[early_stopping_round: 0]
+[early_stopping_min_delta: 0]
+[first_metric_only: 0]
+[max_delta_step: 0]
+[lambda_l1: 0]
+[lambda_l2: 0]
+[linear_lambda: 0]
+[min_gain_to_split: 0]
+[drop_rate: 0.1]
+[max_drop: 50]
+[skip_drop: 0.5]
+[xgboost_dart_mode: 0]
+[uniform_drop: 0]
+[drop_seed: 4]
+[top_rate: 0.2]
+[other_rate: 0.1]
+[min_data_per_group: 100]
+[max_cat_threshold: 32]
+[cat_l2: 10]
+[cat_smooth: 10]
+[max_cat_to_onehot: 4]
+[top_k: 20]
+[monotone_constraints: ]
+[monotone_constraints_method: basic]
+[monotone_penalty: 0]
+[feature_contri: ]
+[forcedsplits_filename: ]
+[refit_decay_rate: 0.9]
+[cegb_tradeoff: 1]
+[cegb_penalty_split: 0]
+[cegb_penalty_feature_lazy: ]
+[cegb_penalty_feature_coupled: ]
+[path_smooth: 0]
+[interaction_constraints: ]
+[verbosity: -1]
+[saved_feature_importance_type: 0]
+[use_quantized_grad: 0]
+[num_grad_quant_bins: 4]
+[quant_train_renew_leaf: 0]
+[stochastic_rounding: 1]
+[linear_tree: 0]
+[max_bin: 255]
+[max_bin_by_feature: ]
+[min_data_in_bin: 3]
+[bin_construct_sample_cnt: 200000]
+[data_random_seed: 1]
+[is_enable_sparse: 1]
+[enable_bundle: 1]
+[use_missing: 1]
+[zero_as_missing: 0]
+[feature_pre_filter: 1]
+[pre_partition: 0]
+[two_round: 0]
+[header: 0]
+[label_column: ]
+[weight_column: ]
+[group_column: ]
+[ignore_column: ]
+[categorical_feature: 24,25,27]
+[forcedbins_filename: ]
+[precise_float_parser: 0]
+[parser_config_file: ]
+[objective_seed: 5]
+[num_class: 1]
+[is_unbalance: 0]
+[scale_pos_weight: 1]
+[sigmoid: 1]
+[boost_from_average: 1]
+[reg_sqrt: 0]
+[alpha: 0.9]
+[fair_c: 1]
+[poisson_max_delta_step: 0.7]
+[tweedie_variance_power: 1.5]
+[lambdarank_truncation_level: 30]
+[lambdarank_norm: 1]
+[label_gain: ]
+[lambdarank_position_bias_regularization: 0]
+[eval_at: ]
+[multi_error_top_k: 1]
+[auc_mu_weights: ]
+[num_machines: 1]
+[local_listen_port: 12400]
+[time_out: 120]
+[machine_list_filename: ]
+[machines: ]
+[gpu_platform_id: -1]
+[gpu_device_id: -1]
+[gpu_use_dp: 0]
+[num_gpu: 1]
+
+end of parameters
+
+pandas_categorical:[[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], [2, 3, 5, 7, 9, 10, 12, 13, 14, 15, 16, 17, 19, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 33, 35, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 49, 51, 52, 55, 57, 59, 60, 61, 62, 64, 66, 68, 69, 70, 71, 72, 74, 75, 78, 79, 80, 83, 84, 85, 86, 87, 89, 91, 93, 95, 96, 98, 99, 100, 101, 102, 103, 105, 107, 108, 109, 110, 112, 113, 114, 116, 118, 119, 121, 123, 124, 127, 128, 129, 133, 135, 136, 138, 140, 142, 144, 146, 150, 152, 153, 154, 155, 158, 160, 161, 164, 165, 167, 172, 173, 174, 225, 235, 247, 253, 268, 273, 277, 281, 287, 288], [2]]