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 +1,20851 @@ +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] 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28 22 21 58 20 +internal_value=0 0.00124221 0.00165986 0.000896964 0.00146217 -0.000259643 0.0735651 -0.000827021 -0.243471 0.0982291 +internal_weight=0 13225 13205 13182 13160 12863 297 12835 114 275 +internal_count=13339 13225 13205 13182 13160 12863 297 12835 114 275 +cat_boundaries=0 4 8 +cat_threshold=16384 0 524544 32 0 16400 1113587712 139264 +is_linear=0 +shrinkage=0.01 + + +end of trees + +feature_importances: +marca_id_encoded=2709 +año=1624 +precio_total_lag_5=1068 +precio_total_lag_1=1009 +mes=903 +precio_total_lag_4=826 +precio_total_lag_2=710 +precio_total_lag_9=687 +precio_total_lag_6=666 +precio_total_lag_11=650 +precio_total_lag_7=623 +precio_total_lag_8=586 +precio_total_lag_3=574 +precio_total_lag_14=247 +precio_total_lag_10=239 +precio_total_lag_12=183 +precio_total_lag_15=173 +precio_total_lag_13=111 +precio_total_lag_19=59 +precio_total_lag_22=51 +precio_total_lag_18=50 +precio_total_lag_21=36 +precio_total_lag_16=30 +precio_total_lag_17=24 +precio_total_lag_20=19 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+[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, 171, 172, 174, 175, 177, 208, 230, 247, 253, 268, 273, 277, 278], [2]]