diff --git "a/models/model_washing_machine.txt" "b/models/model_washing_machine.txt"
new file mode 100644--- /dev/null
+++ "b/models/model_washing_machine.txt"
@@ -0,0 +1,19196 @@
+tree
+version=v4
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+
+Tree=993
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+
+Tree=994
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+
+Tree=995
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+
+Tree=996
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+
+Tree=997
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+
+Tree=998
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+
+Tree=999
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+left_child=5 3 -3 -2 -4 7 -7 9 -9 11 -11 -1
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+internal_value=0 2.17622e-05 9.41961e-05 -9.25561e-05 7.92924e-06 -4.59471e-08 -4.26989e-05 -2.18354e-08 2.39207e-05 -3.49131e-08 -8.83757e-06 -7.44435e-09
+internal_weight=0 132 83 49 62 128532 63 128469 53 128416 353 128063
+internal_count=128664 132 83 49 62 128532 63 128469 53 128416 353 128063
+is_linear=0
+shrinkage=0.0876707
+
+
+end of trees
+
+feature_importances:
+exact_1=2978
+std_1=741
+max_1=730
+min_1=517
+exact_3=505
+mean_1=437
+max_192=336
+max_3=311
+median_1=231
+max_6=223
+median_6=205
+mean_3=202
+min_3=199
+std_3=194
+median_3=192
+mean_96=183
+mean_48=182
+max_48=181
+max_96=179
+std_192=178
+max_12=171
+mean_192=158
+max_24=151
+mean_24=146
+day=145
+std_96=142
+median_12=130
+mean_12=127
+hour_sin=122
+std_24=122
+std_12=121
+mean_6=119
+hour_cos=112
+day_sin=112
+std_6=108
+std_48=104
+day_cos=97
+exact_6=91
+month_cos=78
+hour=74
+month=74
+median_24=74
+day_of_week=58
+min_6=57
+day_of_week_sin=52
+day_of_week_cos=39
+min_12=30
+season=29
+month_sin=24
+exact_12=19
+season_cos=18
+part_of_day=16
+is_working_hours=14
+season_sin=13
+median_48=13
+median_96=12
+median_192=4
+is_weekend=1
+
+parameters:
+[boosting: gbdt]
+[objective: regression]
+[metric: l2]
+[tree_learner: serial]
+[device_type: cpu]
+[data_sample_strategy: bagging]
+[data: ]
+[valid: ]
+[num_iterations: 1000]
+[learning_rate: 0.0876707]
+[num_leaves: 30]
+[num_threads: 0]
+[seed: 0]
+[deterministic: 0]
+[force_col_wise: 0]
+[force_row_wise: 0]
+[histogram_pool_size: -1]
+[max_depth: 5]
+[min_data_in_leaf: 20]
+[min_sum_hessian_in_leaf: 0.00473012]
+[bagging_fraction: 0.667959]
+[pos_bagging_fraction: 1]
+[neg_bagging_fraction: 1]
+[bagging_freq: 2]
+[bagging_seed: 3]
+[feature_fraction: 0.835634]
+[feature_fraction_bynode: 1]
+[feature_fraction_seed: 2]
+[extra_trees: 0]
+[extra_seed: 6]
+[early_stopping_round: 0]
+[first_metric_only: 0]
+[max_delta_step: 0]
+[lambda_l1: 0.00468075]
+[lambda_l2: 0.00260979]
+[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: ]
+[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:[]