diff --git "a/forecasting/colab_model_train.ipynb" "b/forecasting/colab_model_train.ipynb" new file mode 100644--- /dev/null +++ "b/forecasting/colab_model_train.ipynb" @@ -0,0 +1,11450 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "MMHkv6MqYL0z" + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "_fdfg5W6YL00", + "outputId": "89bc6702-c282-4f2f-88d8-f93b251ce00c" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\karlo\\AppData\\Local\\Temp\\ipykernel_11020\\3466840311.py:1: DtypeWarning: Columns (3,12,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,37,41,42,44) have mixed types. Specify dtype option on import or set low_memory=False.\n", + " data_normal = pd.read_csv('.\\data\\для анализа\\dataset._normal.csv', delimiter=';')\n" + ] + } + ], + "source": [ + "data_normal = pd.read_csv('.\\data\\для анализа\\dataset._normal.csv', delimiter=';')\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "yf308r_QYL00" + }, + "outputs": [], + "source": [ + "data_normal[\"Рабочий\"] = 1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "eE6kVD4YYL01", + "outputId": "fd86ce39-d7a1-46f4-ddfd-645b99d665d7" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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Дата и времяПолож.пед.акселер.,%Нагрузка на двигатель, %Давл.масла двиг.,кПаТемп.масла двиг.,°СОбор.двиг.,об/минЗначение счетчика моточасов, час:минСост.пед.сцепл.iButton2КПП. Температура масла...Холодный старт (spn3871)Крутящий момент (spn513), НмПоложение рейки ТНВД (spn51), %Расход топлива (spn183), л/чДВС. Температура наддувочного воздуха, °СДавление наддувочного воздуха двигателя (spn106), кПаТекущая передача (spn523)Температура масла гидравлики (spn5536), СПедаль слива (spn598)Рабочий
001/06/2023 00:28:27-------NaN-...---------1
101/06/2023 01:29:33-------NaN-...---------1
201/06/2023 01:29:45-------NaN-...---------1
301/06/2023 04:46:32-------NaN-...---------1
401/06/2023 04:47:01-------NaN-...---------1
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226320224/08/2023 11:46:040,0-528-273,0001885,500-Отпущ.NaN-...---------2
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226320524/08/2023 11:46:010,0-528-273,0001916,2501380:24Отпущ.NaN-...---------2
226320624/08/2023 11:46:000,0-528-273,0001900,750-Отпущ.NaN-...---------2
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Дата и времяПолож.пед.акселер.,%Нагрузка на двигатель, %Давл.масла двиг.,кПаТемп.масла двиг.,°СОбор.двиг.,об/минЗначение счетчика моточасов, час:минСост.пед.сцепл.iButton2КПП. Температура масла...Холодный старт (spn3871)Крутящий момент (spn513), НмПоложение рейки ТНВД (spn51), %Расход топлива (spn183), л/чДВС. Температура наддувочного воздуха, °СДавление наддувочного воздуха двигателя (spn106), кПаТекущая передача (spn523)Температура масла гидравлики (spn5536), СПедаль слива (spn598)Рабочий
001/06/2023 00:28:27NaNNaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNNaNNaN1
101/06/2023 01:29:33NaNNaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNNaNNaN1
201/06/2023 01:29:45NaNNaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNNaNNaN1
301/06/2023 04:46:32NaNNaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaNNaNNaNNaN1
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" + ], + "text/plain": [ + " Дата и время Полож.пед.акселер.,% Нагрузка на двигатель, % \\\n", + "0 01/06/2023 07:57:01 0,0 NaN \n", + "1 01/06/2023 07:57:31 0,0 NaN \n", + "2 01/06/2023 07:58:01 0,0 NaN \n", + "3 01/06/2023 07:58:31 0,0 NaN \n", + "4 01/06/2023 07:59:01 0,0 NaN \n", + "... ... ... ... \n", + "2856638 18/05/2023 23:56:40 8,0 NaN \n", + "2856639 18/05/2023 23:57:10 82,0 NaN \n", + "2856640 18/05/2023 23:57:36 10,0 NaN \n", + "2856641 18/05/2023 23:58:06 22,0 NaN \n", + "2856642 18/05/2023 23:58:36 55,0 NaN \n", + "\n", + " Давл.масла двиг.,кПа Темп.масла двиг.,°С Обор.двиг.,об/мин \\\n", + "0 0 NaN 0,000 \n", + "1 380 NaN 649,000 \n", + "2 360 NaN 651,000 \n", + "3 348 NaN 656,000 \n", + "4 360 NaN 671,875 \n", + "... ... ... ... \n", + "2856638 458 6 3350,000 \n", + "2856639 941 105 2778,000 \n", + "2856640 1187 182 2518,000 \n", + "2856641 1199 65 1291,000 \n", + "2856642 751 181 4770,000 \n", + "\n", + " Значение счетчика моточасов, час:мин Сост.пед.сцепл. iButton2 \\\n", + "0 NaN Отпущ. NaN \n", + "1 422:24 Отпущ. NaN \n", + "2 422:24 Отпущ. NaN \n", + "3 422:24 Отпущ. NaN \n", + "4 422:24 Отпущ. NaN \n", + "... ... ... ... \n", + "2856638 168:36 Отпущ. NaN \n", + "2856639 168:36 Отпущ. NaN \n", + "2856640 168:36 Отпущ. NaN \n", + "2856641 168:36 Отпущ. NaN \n", + "2856642 168:36 Отпущ. NaN \n", + "\n", + " КПП. Температура масла ... Холодный старт (spn3871) \\\n", + "0 NaN ... NaN \n", + "1 NaN ... NaN \n", + "2 NaN ... NaN \n", + "3 NaN ... NaN \n", + "4 NaN ... NaN \n", + "... ... ... ... \n", + "2856638 -238.0 ... 0 \n", + "2856639 -171.0 ... 0 \n", + "2856640 -197.0 ... 0 \n", + "2856641 -61.0 ... 0 \n", + "2856642 -12.0 ... 0 \n", + "\n", + " Крутящий момент (spn513), Нм Положение рейки ТНВД (spn51), % \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN NaN \n", + "4 NaN NaN \n", + "... ... ... \n", + "2856638 NaN NaN \n", + "2856639 NaN NaN \n", + "2856640 NaN NaN \n", + "2856641 NaN NaN \n", + "2856642 NaN NaN \n", + "\n", + " Расход топлива (spn183), л/ч \\\n", + "0 NaN \n", + "1 NaN \n", + "2 NaN \n", + "3 NaN \n", + "4 NaN \n", + "... ... \n", + "2856638 NaN \n", + "2856639 NaN \n", + "2856640 NaN \n", + "2856641 NaN \n", + "2856642 NaN \n", + "\n", + " ДВС. Температура наддувочного воздуха, °С \\\n", + "0 NaN \n", + "1 NaN \n", + "2 NaN \n", + "3 NaN \n", + "4 NaN \n", + "... ... \n", + "2856638 NaN \n", + "2856639 NaN \n", + "2856640 NaN \n", + "2856641 NaN \n", + "2856642 NaN \n", + "\n", + " Давление наддувочного воздуха двигателя (spn106), кПа \\\n", + "0 NaN \n", + "1 NaN \n", + "2 NaN \n", + "3 NaN \n", + "4 NaN \n", + "... ... \n", + "2856638 NaN \n", + "2856639 NaN \n", + "2856640 NaN \n", + "2856641 NaN \n", + "2856642 NaN \n", + "\n", + " Текущая передача (spn523) Температура масла гидравлики (spn5536), С \\\n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN NaN \n", + "4 NaN NaN \n", + "... ... ... \n", + "2856638 NaN NaN \n", + "2856639 NaN NaN \n", + "2856640 NaN NaN \n", + "2856641 NaN NaN \n", + "2856642 NaN NaN \n", + "\n", + " Педаль слива (spn598) Рабочий \n", + "0 NaN 1 \n", + "1 NaN 1 \n", + "2 NaN 1 \n", + "3 NaN 1 \n", + "4 NaN 1 \n", + "... ... ... \n", + "2856638 NaN 3 \n", + "2856639 NaN 3 \n", + "2856640 NaN 3 \n", + "2856641 NaN 3 \n", + "2856642 NaN 3 \n", + "\n", + "[2834231 rows x 56 columns]" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "combinet" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ZOegh2rYYL03" + }, + "outputs": [], + "source": [ + "combinet = combinet.drop(columns=['Дата и время', 'iButton2','Нагрузка на двигатель, %', 'Крутящий момент (spn513), Нм', 'Положение рейки ТНВД (spn51), %' , 'Расход топлива (spn183), л/ч', 'ДВС. Температура наддувочного воздуха, °С', 'Давление наддувочного возд��ха двигателя (spn106), кПа', 'Текущая передача (spn523)', 'Температура масла гидравлики (spn5536), С', 'Педаль слива (spn598)'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Lr3K-P1OYL03" + }, + "outputs": [], + "source": [ + "combinet[\"Сост.пед.сцепл.\"] = combinet[\"Сост.пед.сцепл.\"].astype(bool)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "UZLpym0sYL03" + }, + "outputs": [], + "source": [ + "combinet['Обор.двиг.,об/мин'] = combinet['Обор.двиг.,об/мин'].str.replace(',', '.').astype(float)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "GWauhUWAYL04" + }, + "outputs": [], + "source": [ + "combinet['Значение счетчика моточасов, час:мин'] = combinet['Значение счетчика моточасов, час:мин'].str.replace(':', '').astype(float)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "id": "T7GWt_P7YL04" + }, + "outputs": [], + "source": [ + "combinet['Сост.пед.сцепл.'] = combinet['Сост.пед.сцепл.'].replace(',', '.').astype(float)\n", + "combinet['Сост.пед.сцепл.'] = combinet['Сост.пед.сцепл.'].astype(str)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "CkRWTcQIYL04" + }, + "outputs": [], + "source": [ + "combinet['Полож.пед.акселер.,%'] = combinet['Полож.пед.акселер.,%'].str.replace(',', '.').astype(float)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "81zw6h8sYL04" + }, + "outputs": [], + "source": [ + "combinet['Темп.масла двиг.,°С'] = combinet['Темп.масла двиг.,°С'].str.replace(',', '.').astype(float)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "UWKl2pnAYL04" + }, + "outputs": [], + "source": [ + "combinet['КПП. Температура масла'] = combinet['КПП. Температура масла'].astype(float)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "DAPlGXPZYL04" + }, + "outputs": [], + "source": [ + "combinet.drop(['Нейтраль КПП (spn3843)', 'Стояночный тормоз (spn3842)', 'Аварийная температура охлаждающей жидкости (spn3841)', 'Засоренность воздушного фильтра (spn3840)', 'Засоренность фильтра КПП (spn3847)', 'Аварийное давление масла ДВС (spn3846)',\n", + " 'Засоренность фильтра ДВС (spn3845)',\n", + " 'Засоренность фильтра рулевого управления (spn3844)',\n", + " 'Засоренность фильтра навесного оборудования (spn3851)',\n", + " 'Недопустимый уровень масла в гидробаке (spn3850)',\n", + " 'Аварийная температура масла в гидросистеме (spn3849)',\n", + " 'Аварийное давление в I контуре тормозной системы (spn3848)',\n", + " 'Аварийное давление в II контуре тормозной системы (spn3855)',\n", + " 'Зарядка АКБ (spn3854)', 'Отопитель (spn3853)',\n", + " 'Выход блока управления двигателем (spn3852)',\n", + " 'Включение тормозков (spn3859)', 'Засоренность фильтра слива (spn3858)',\n", + " 'Аварийное давление масла КПП (spn3857)',\n", + " 'Аварийная температура масла ДВС(spn3856)',\n", + " 'Неисправность тормозной системы (spn3863)', 'Термостарт (spn3862)',\n", + " 'Разрешение запуска двигателя (spn3861)', 'Низкий уровень ОЖ (spn3860)',\n", + " 'Аварийная температура масла ГТР (spn3867)',\n", + " 'Необходимость сервисного обслуживания (spn3866)',\n", + " 'Подогрев топливного фильтра (spn3865)', 'Вода в топливе (spn3864)',\n", + " 'Холодный старт (spn3871)'], axis=1, inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "id": "Nw3GKn5SYL04" + }, + "outputs": [], + "source": [ + "cat_cols =['Сост.пед.сцепл.']" + ] + }, + { + "cell_type": "code", + "source": [ + "!pip install ipympl" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "J81WqvgMajWz", + "outputId": "5859b6e7-eec7-496e-ef71-06282df7eb53" + }, + "execution_count": 27, 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ipympl-0.9.3 jedi-0.19.1\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from catboost import CatBoostClassifier\n", + "\n", + "import pandas as pd\n", + "import numpy as np\n", + "from google.colab import output\n", + "output.disable_custom_widget_manager()\n", + "%matplotlib inline\n", + "%matplotlib widget" + ], + "metadata": { + "id": "9pjahM2pZ6ze" + }, + "execution_count": 32, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "!unzip /content/dataset.zip" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "v2xiSVszbZ1v", + "outputId": "1a14a432-30e1-4de3-b919-b3df10eec0ca" + }, + "execution_count": 7, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Archive: /content/dataset.zip\n", + " inflating: dataset.csv \n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "combinet = pd.read_csv(\"/content/dataset.csv\")" + ], + "metadata": { + "id": "17J47bPodeD1" + }, + "execution_count": 16, + "outputs": [] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "id": "wD74qy8qYL05" + }, + "outputs": [], + "source": [ + "X_train, X_test, y_train, y_test = train_test_split(combinet.drop(['Рабочий'], axis=1), combinet['Рабочий'], test_size = 0.1, random_state = 69)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000, + "referenced_widgets": [ + "aa393e98c6ef47b58dc10a5b91aab35d" + ] + }, + "id": "N3a5wulKYL05", + "outputId": "41892796-14e6-4cb3-9de9-1fdb0924c910" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))" + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "aa393e98c6ef47b58dc10a5b91aab35d" + } + }, + "metadata": {} 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0.9973820\tbest: 0.9973820 (12900)\ttotal: 6m 43s\tremaining: 19m 21s\n", + "13000:\tlearn: 0.9981802\ttest: 0.9973961\tbest: 0.9973961 (13000)\ttotal: 6m 46s\tremaining: 19m 16s\n", + "13100:\tlearn: 0.9981841\ttest: 0.9974032\tbest: 0.9974032 (13100)\ttotal: 6m 49s\tremaining: 19m 12s\n", + "13200:\tlearn: 0.9981888\ttest: 0.9974032\tbest: 0.9974032 (13100)\ttotal: 6m 52s\tremaining: 19m 10s\n", + "13300:\tlearn: 0.9981919\ttest: 0.9974067\tbest: 0.9974067 (13300)\ttotal: 6m 56s\tremaining: 19m 8s\n", + "13400:\tlearn: 0.9981931\ttest: 0.9974032\tbest: 0.9974067 (13300)\ttotal: 6m 58s\tremaining: 19m 3s\n", + "13500:\tlearn: 0.9982029\ttest: 0.9973961\tbest: 0.9974067 (13300)\ttotal: 7m 1s\tremaining: 18m 59s\n", + "13600:\tlearn: 0.9982104\ttest: 0.9974032\tbest: 0.9974067 (13300)\ttotal: 7m 4s\tremaining: 18m 54s\n", + "13700:\tlearn: 0.9982115\ttest: 0.9974208\tbest: 0.9974208 (13700)\ttotal: 7m 8s\tremaining: 18m 55s\n", + "13800:\tlearn: 0.9982198\ttest: 0.9974455\tbest: 0.9974455 (13800)\ttotal: 7m 11s\tremaining: 18m 51s\n", + "13900:\tlearn: 0.9982233\ttest: 0.9974491\tbest: 0.9974491 (13900)\ttotal: 7m 13s\tremaining: 18m 46s\n", + "14000:\tlearn: 0.9982261\ttest: 0.9974455\tbest: 0.9974491 (13900)\ttotal: 7m 16s\tremaining: 18m 42s\n", + "14100:\tlearn: 0.9982351\ttest: 0.9974455\tbest: 0.9974491 (13900)\ttotal: 7m 21s\tremaining: 18m 42s\n", + "14200:\tlearn: 0.9982366\ttest: 0.9974596\tbest: 0.9974596 (14200)\ttotal: 7m 23s\tremaining: 18m 38s\n", + "14300:\tlearn: 0.9982406\ttest: 0.9974667\tbest: 0.9974667 (14300)\ttotal: 7m 26s\tremaining: 18m 34s\n", + "14400:\tlearn: 0.9982476\ttest: 0.9974632\tbest: 0.9974667 (14300)\ttotal: 7m 28s\tremaining: 18m 29s\n", + "14500:\tlearn: 0.9982531\ttest: 0.9974667\tbest: 0.9974667 (14300)\ttotal: 7m 33s\tremaining: 18m 29s\n", + "14600:\tlearn: 0.9982558\ttest: 0.9974667\tbest: 0.9974667 (14300)\ttotal: 7m 36s\tremaining: 18m 26s\n", + "14700:\tlearn: 0.9982594\ttest: 0.9974667\tbest: 0.9974667 (14300)\ttotal: 7m 38s\tremaining: 18m 21s\n", + "14800:\tlearn: 0.9982676\ttest: 0.9974667\tbest: 0.9974667 (14300)\ttotal: 7m 41s\tremaining: 18m 17s\n", + "14900:\tlearn: 0.9982723\ttest: 0.9974702\tbest: 0.9974702 (14900)\ttotal: 7m 44s\tremaining: 18m 13s\n", + "15000:\tlearn: 0.9982747\ttest: 0.9974667\tbest: 0.9974702 (14900)\ttotal: 7m 48s\tremaining: 18m 13s\n", + "15100:\tlearn: 0.9982782\ttest: 0.9974737\tbest: 0.9974737 (15100)\ttotal: 7m 51s\tremaining: 18m 8s\n", + "15200:\tlearn: 0.9982856\ttest: 0.9974702\tbest: 0.9974737 (15100)\ttotal: 7m 53s\tremaining: 18m 4s\n", + "15300:\tlearn: 0.9982884\ttest: 0.9974773\tbest: 0.9974773 (15300)\ttotal: 7m 56s\tremaining: 18m\n", + "15400:\tlearn: 0.9982915\ttest: 0.9974702\tbest: 0.9974773 (15300)\ttotal: 8m\tremaining: 18m\n", + "15500:\tlearn: 0.9982962\ttest: 0.9974773\tbest: 0.9974773 (15300)\ttotal: 8m 3s\tremaining: 17m 56s\n", + "15600:\tlearn: 0.9982994\ttest: 0.9974808\tbest: 0.9974808 (15600)\ttotal: 8m 6s\tremaining: 17m 52s\n", + "15700:\tlearn: 0.9983052\ttest: 0.9974879\tbest: 0.9974879 (15700)\ttotal: 8m 8s\tremaining: 17m 47s\n", + "15800:\tlearn: 0.9983072\ttest: 0.9974843\tbest: 0.9974879 (15700)\ttotal: 8m 13s\tremaining: 17m 47s\n", + "15900:\tlearn: 0.9983123\ttest: 0.9974843\tbest: 0.9974879 (15700)\ttotal: 8m 15s\tremaining: 17m 43s\n", + "16000:\tlearn: 0.9983127\ttest: 0.9974843\tbest: 0.9974879 (15700)\ttotal: 8m 18s\tremaining: 17m 39s\n", + "16100:\tlearn: 0.9983166\ttest: 0.9974949\tbest: 0.9974949 (16100)\ttotal: 8m 21s\tremaining: 17m 35s\n", + "16200:\tlearn: 0.9983201\ttest: 0.9974984\tbest: 0.9974984 (16200)\ttotal: 8m 24s\tremaining: 17m 32s\n", + "16300:\tlearn: 0.9983229\ttest: 0.9974984\tbest: 0.9974984 (16200)\ttotal: 8m 28s\tremaining: 17m 30s\n", + "16400:\tlearn: 0.9983311\ttest: 0.9975020\tbest: 0.9975020 (16400)\ttotal: 8m 31s\tremaining: 17m 26s\n", + "16500:\tlearn: 0.9983378\ttest: 0.9975055\tbest: 0.9975055 (16500)\ttotal: 8m 33s\tremaining: 17m 22s\n", + "16600:\tlearn: 0.9983437\ttest: 0.9975055\tbest: 0.9975055 (16500)\ttotal: 8m 36s\tremaining: 17m 18s\n", + "16700:\tlearn: 0.9983452\ttest: 0.9975161\tbest: 0.9975161 (16700)\ttotal: 8m 40s\tremaining: 17m 18s\n", + "16800:\tlearn: 0.9983488\ttest: 0.9975090\tbest: 0.9975161 (16700)\ttotal: 8m 43s\tremaining: 17m 14s\n", + "16900:\tlearn: 0.9983515\ttest: 0.9975161\tbest: 0.9975161 (16700)\ttotal: 8m 46s\tremaining: 17m 10s\n", + "17000:\tlearn: 0.9983546\ttest: 0.9975161\tbest: 0.9975161 (16700)\ttotal: 8m 48s\tremaining: 17m 6s\n", + "17100:\tlearn: 0.9983586\ttest: 0.9975126\tbest: 0.9975161 (16700)\ttotal: 8m 52s\tremaining: 17m 5s\n", + "17200:\tlearn: 0.9983605\ttest: 0.9975161\tbest: 0.9975161 (16700)\ttotal: 8m 55s\tremaining: 17m 1s\n", + "17300:\tlearn: 0.9983640\ttest: 0.9975126\tbest: 0.9975161 (16700)\ttotal: 8m 58s\tremaining: 16m 57s\n", + "17400:\tlearn: 0.9983688\ttest: 0.9975231\tbest: 0.9975231 (17400)\ttotal: 9m 1s\tremaining: 16m 53s\n", + "17500:\tlearn: 0.9983672\ttest: 0.9975161\tbest: 0.9975231 (17400)\ttotal: 9m 4s\tremaining: 16m 50s\n", + "17600:\tlearn: 0.9983735\ttest: 0.9975196\tbest: 0.9975231 (17400)\ttotal: 9m 8s\tremaining: 16m 48s\n", + "17700:\tlearn: 0.9983731\ttest: 0.9975196\tbest: 0.9975231 (17400)\ttotal: 9m 10s\tremaining: 16m 44s\n", + "17800:\tlearn: 0.9983774\ttest: 0.9975196\tbest: 0.9975231 (17400)\ttotal: 9m 13s\tremaining: 16m 41s\n", + "17900:\tlearn: 0.9983770\ttest: 0.9975231\tbest: 0.9975231 (17400)\ttotal: 9m 16s\tremaining: 16m 37s\n", + "18000:\tlearn: 0.9983793\ttest: 0.9975231\tbest: 0.9975231 (17400)\ttotal: 9m 20s\tremaining: 16m 36s\n", + "18100:\tlearn: 0.9983829\ttest: 0.9975302\tbest: 0.9975302 (18100)\ttotal: 9m 23s\tremaining: 16m 32s\n", + "18200:\tlearn: 0.9983872\ttest: 0.9975231\tbest: 0.9975302 (18100)\ttotal: 9m 25s\tremaining: 16m 28s\n", + "18300:\tlearn: 0.9983899\ttest: 0.9975302\tbest: 0.9975302 (18100)\ttotal: 9m 28s\tremaining: 16m 24s\n", + "18400:\tlearn: 0.9983978\ttest: 0.9975196\tbest: 0.9975302 (18100)\ttotal: 9m 32s\tremaining: 16m 23s\n", + "18500:\tlearn: 0.9984029\ttest: 0.9975196\tbest: 0.9975302 (18100)\ttotal: 9m 35s\tremaining: 16m 19s\n", + "18600:\tlearn: 0.9984048\ttest: 0.9975267\tbest: 0.9975302 (18100)\ttotal: 9m 38s\tremaining: 16m 16s\n", + "18700:\tlearn: 0.9984087\ttest: 0.9975231\tbest: 0.9975302 (18100)\ttotal: 9m 40s\tremaining: 16m 12s\n", + "18800:\tlearn: 0.9984142\ttest: 0.9975267\tbest: 0.9975302 (18100)\ttotal: 9m 43s\tremaining: 16m 9s\n", + "18900:\tlearn: 0.9984174\ttest: 0.9975267\tbest: 0.9975302 (18100)\ttotal: 9m 47s\tremaining: 16m 7s\n", + "19000:\tlearn: 0.9984193\ttest: 0.9975373\tbest: 0.9975373 (19000)\ttotal: 9m 50s\tremaining: 16m 3s\n", + "19100:\tlearn: 0.9984221\ttest: 0.9975302\tbest: 0.9975373 (19000)\ttotal: 9m 53s\tremaining: 15m 59s\n", + "19200:\tlearn: 0.9984279\ttest: 0.9975267\tbest: 0.9975373 (19000)\ttotal: 9m 55s\tremaining: 15m 55s\n", + "19300:\tlearn: 0.9984303\ttest: 0.9975337\tbest: 0.9975373 (19000)\ttotal: 10m\tremaining: 15m 54s\n", + "19400:\tlearn: 0.9984315\ttest: 0.9975267\tbest: 0.9975373 (19000)\ttotal: 10m 2s\tremaining: 15m 50s\n", + "19500:\tlearn: 0.9984342\ttest: 0.9975337\tbest: 0.9975373 (19000)\ttotal: 10m 5s\tremaining: 15m 46s\n", + "19600:\tlearn: 0.9984358\ttest: 0.9975337\tbest: 0.9975373 (19000)\ttotal: 10m 8s\tremaining: 15m 43s\n", + "19700:\tlearn: 0.9984366\ttest: 0.9975373\tbest: 0.9975373 (19000)\ttotal: 10m 12s\tremaining: 15m 41s\n", + "19800:\tlearn: 0.9984409\ttest: 0.9975408\tbest: 0.9975408 (19800)\ttotal: 10m 15s\tremaining: 15m 38s\n", + "19900:\tlearn: 0.9984425\ttest: 0.9975443\tbest: 0.9975443 (19900)\ttotal: 10m 17s\tremaining: 15m 34s\n", + "20000:\tlearn: 0.9984472\ttest: 0.9975443\tbest: 0.9975443 (19900)\ttotal: 10m 20s\tremaining: 15m 30s\n", + "20100:\tlearn: 0.9984499\ttest: 0.9975443\tbest: 0.9975443 (19900)\ttotal: 10m 23s\tremaining: 15m 27s\n", + "20200:\tlearn: 0.9984562\ttest: 0.9975478\tbest: 0.9975478 (20200)\ttotal: 10m 27s\tremaining: 15m 25s\n", + "20300:\tlearn: 0.9984609\ttest: 0.9975478\tbest: 0.9975478 (20200)\ttotal: 10m 30s\tremaining: 15m 21s\n", + "20400:\tlearn: 0.9984617\ttest: 0.9975443\tbest: 0.9975478 (20200)\ttotal: 10m 32s\tremaining: 15m 17s\n", + "20500:\tlearn: 0.9984644\ttest: 0.9975443\tbest: 0.9975478 (20200)\ttotal: 10m 35s\tremaining: 15m 14s\n", + "20600:\tlearn: 0.9984707\ttest: 0.9975478\tbest: 0.9975478 (20200)\ttotal: 10m 39s\tremaining: 15m 12s\n", + "20700:\tlearn: 0.9984726\ttest: 0.9975478\tbest: 0.9975478 (20200)\ttotal: 10m 42s\tremaining: 15m 8s\n", + "20800:\tlearn: 0.9984754\ttest: 0.9975514\tbest: 0.9975514 (20800)\ttotal: 10m 44s\tremaining: 15m 5s\n", + "20900:\tlearn: 0.9984793\ttest: 0.9975584\tbest: 0.9975584 (20900)\ttotal: 10m 47s\tremaining: 15m 1s\n", + "21000:\tlearn: 0.9984832\ttest: 0.9975620\tbest: 0.9975620 (21000)\ttotal: 10m 51s\tremaining: 14m 59s\n", + "21100:\tlearn: 0.9984836\ttest: 0.9975549\tbest: 0.9975620 (21000)\ttotal: 10m 54s\tremaining: 14m 56s\n", + "21200:\tlearn: 0.9984864\ttest: 0.9975584\tbest: 0.9975620 (21000)\ttotal: 10m 57s\tremaining: 14m 52s\n", + "21300:\tlearn: 0.9984891\ttest: 0.9975584\tbest: 0.9975620 (21000)\ttotal: 10m 59s\tremaining: 14m 48s\n", + "21400:\tlearn: 0.9984911\ttest: 0.9975584\tbest: 0.9975620 (21000)\ttotal: 11m 2s\tremaining: 14m 45s\n", + "21500:\tlearn: 0.9984926\ttest: 0.9975655\tbest: 0.9975655 (21500)\ttotal: 11m 6s\tremaining: 14m 43s\n", + "21600:\tlearn: 0.9984966\ttest: 0.9975690\tbest: 0.9975690 (21600)\ttotal: 11m 9s\tremaining: 14m 39s\n", + "21700:\tlearn: 0.9984966\ttest: 0.9975725\tbest: 0.9975725 (21700)\ttotal: 11m 11s\tremaining: 14m 36s\n", + "21800:\tlearn: 0.9984993\ttest: 0.9975690\tbest: 0.9975725 (21700)\ttotal: 11m 14s\tremaining: 14m 32s\n", + "21900:\tlearn: 0.9985013\ttest: 0.9975725\tbest: 0.9975725 (21700)\ttotal: 11m 18s\tremaining: 14m 31s\n", + "22000:\tlearn: 0.9985083\ttest: 0.9975761\tbest: 0.9975761 (22000)\ttotal: 11m 21s\tremaining: 14m 27s\n", + "22100:\tlearn: 0.9985099\ttest: 0.9975796\tbest: 0.9975796 (22100)\ttotal: 11m 24s\tremaining: 14m 23s\n", + "22200:\tlearn: 0.9985122\ttest: 0.9975831\tbest: 0.9975831 (22200)\ttotal: 11m 26s\tremaining: 14m 20s\n", + "22300:\tlearn: 0.9985162\ttest: 0.9975867\tbest: 0.9975867 (22300)\ttotal: 11m 30s\tremaining: 14m 17s\n", + "22400:\tlearn: 0.9985173\ttest: 0.9975831\tbest: 0.9975867 (22300)\ttotal: 11m 33s\tremaining: 14m 14s\n", + "22500:\tlearn: 0.9985177\ttest: 0.9975937\tbest: 0.9975937 (22500)\ttotal: 11m 36s\tremaining: 14m 11s\n", + "22600:\tlearn: 0.9985185\ttest: 0.9975902\tbest: 0.9975937 (22500)\ttotal: 11m 39s\tremaining: 14m 7s\n", + "22700:\tlearn: 0.9985236\ttest: 0.9975972\tbest: 0.9975972 (22700)\ttotal: 11m 41s\tremaining: 14m 3s\n", + "22800:\tlearn: 0.9985271\ttest: 0.9976008\tbest: 0.9976008 (22800)\ttotal: 11m 46s\tremaining: 14m 2s\n", + "22900:\tlearn: 0.9985271\ttest: 0.9976008\tbest: 0.9976008 (22800)\ttotal: 11m 48s\tremaining: 13m 58s\n", + "23000:\tlearn: 0.9985303\ttest: 0.9975902\tbest: 0.9976008 (22800)\ttotal: 11m 51s\tremaining: 13m 55s\n", + "23100:\tlearn: 0.9985326\ttest: 0.9976008\tbest: 0.9976008 (22800)\ttotal: 11m 54s\tremaining: 13m 51s\n", + "23200:\tlearn: 0.9985350\ttest: 0.9976008\tbest: 0.9976008 (22800)\ttotal: 11m 58s\tremaining: 13m 49s\n", + "23300:\tlearn: 0.9985373\ttest: 0.9976043\tbest: 0.9976043 (23300)\ttotal: 12m 1s\tremaining: 13m 46s\n", + "23400:\tlearn: 0.9985409\ttest: 0.9976043\tbest: 0.9976043 (23300)\ttotal: 12m 3s\tremaining: 13m 42s\n", + "23500:\tlearn: 0.9985444\ttest: 0.9976008\tbest: 0.9976043 (23300)\ttotal: 12m 6s\tremaining: 13m 38s\n", + "23600:\tlearn: 0.9985456\ttest: 0.9976008\tbest: 0.9976043 (23300)\ttotal: 12m 9s\tremaining: 13m 35s\n", + "23700:\tlearn: 0.9985499\ttest: 0.9976078\tbest: 0.9976078 (23700)\ttotal: 12m 13s\tremaining: 13m 33s\n", + "23800:\tlearn: 0.9985522\ttest: 0.9976008\tbest: 0.9976078 (23700)\ttotal: 12m 15s\tremaining: 13m 29s\n", + "23900:\tlearn: 0.9985573\ttest: 0.9976184\tbest: 0.9976184 (23900)\ttotal: 12m 18s\tremaining: 13m 26s\n", + "24000:\tlearn: 0.9985581\ttest: 0.9976219\tbest: 0.9976219 (24000)\ttotal: 12m 21s\tremaining: 13m 22s\n", + "24100:\tlearn: 0.9985581\ttest: 0.9976325\tbest: 0.9976325 (24100)\ttotal: 12m 25s\tremaining: 13m 21s\n", + "24200:\tlearn: 0.9985644\ttest: 0.9976290\tbest: 0.9976325 (24100)\ttotal: 12m 28s\tremaining: 13m 17s\n", + "24300:\tlearn: 0.9985640\ttest: 0.9976325\tbest: 0.9976325 (24100)\ttotal: 12m 30s\tremaining: 13m 13s\n", + "24400:\tlearn: 0.9985683\ttest: 0.9976255\tbest: 0.9976325 (24100)\ttotal: 12m 33s\tremaining: 13m 10s\n", + "24500:\tlearn: 0.9985714\ttest: 0.9976290\tbest: 0.9976325 (24100)\ttotal: 12m 37s\tremaining: 13m 7s\n", + "24600:\tlearn: 0.9985706\ttest: 0.9976290\tbest: 0.9976325 (24100)\ttotal: 12m 40s\tremaining: 13m 4s\n", + "24700:\tlearn: 0.9985746\ttest: 0.9976255\tbest: 0.9976325 (24100)\ttotal: 12m 42s\tremaining: 13m 1s\n", + "24800:\tlearn: 0.9985777\ttest: 0.9976219\tbest: 0.9976325 (24100)\ttotal: 12m 45s\tremaining: 12m 57s\n", + "24900:\tlearn: 0.9985789\ttest: 0.9976290\tbest: 0.9976325 (24100)\ttotal: 12m 48s\tremaining: 12m 54s\n", + "25000:\tlearn: 0.9985801\ttest: 0.9976361\tbest: 0.9976361 (25000)\ttotal: 12m 52s\tremaining: 12m 52s\n", + "25100:\tlearn: 0.9985840\ttest: 0.9976219\tbest: 0.9976361 (25000)\ttotal: 12m 55s\tremaining: 12m 48s\n", + "25200:\tlearn: 0.9985832\ttest: 0.9976431\tbest: 0.9976431 (25200)\ttotal: 12m 57s\tremaining: 12m 45s\n", + "25300:\tlearn: 0.9985879\ttest: 0.9976396\tbest: 0.9976431 (25200)\ttotal: 13m\tremaining: 12m 41s\n", + "25400:\tlearn: 0.9985875\ttest: 0.9976361\tbest: 0.9976431 (25200)\ttotal: 13m 4s\tremaining: 12m 39s\n", + "25500:\tlearn: 0.9985930\ttest: 0.9976290\tbest: 0.9976431 (25200)\ttotal: 13m 7s\tremaining: 12m 36s\n", + "25600:\tlearn: 0.9985973\ttest: 0.9976325\tbest: 0.9976431 (25200)\ttotal: 13m 9s\tremaining: 12m 32s\n", + "25700:\tlearn: 0.9985985\ttest: 0.9976431\tbest: 0.9976431 (25200)\ttotal: 13m 12s\tremaining: 12m 29s\n", + "25800:\tlearn: 0.9986016\ttest: 0.9976361\tbest: 0.9976431 (25200)\ttotal: 13m 15s\tremaining: 12m 26s\n", + "25900:\tlearn: 0.9986055\ttest: 0.9976466\tbest: 0.9976466 (25900)\ttotal: 13m 19s\tremaining: 12m 23s\n", + "26000:\tlearn: 0.9986055\ttest: 0.9976466\tbest: 0.9976466 (25900)\ttotal: 13m 22s\tremaining: 12m 20s\n", + "26100:\tlearn: 0.9986091\ttest: 0.9976537\tbest: 0.9976537 (26100)\ttotal: 13m 24s\tremaining: 12m 16s\n", + "26200:\tlearn: 0.9986102\ttest: 0.9976466\tbest: 0.9976537 (26100)\ttotal: 13m 27s\tremaining: 12m 13s\n", + "26300:\tlearn: 0.9986126\ttest: 0.9976572\tbest: 0.9976572 (26300)\ttotal: 13m 31s\tremaining: 12m 11s\n", + "26400:\tlearn: 0.9986138\ttest: 0.9976466\tbest: 0.9976572 (26300)\ttotal: 13m 34s\tremaining: 12m 7s\n", + "26500:\tlearn: 0.9986149\ttest: 0.9976466\tbest: 0.9976572 (26300)\ttotal: 13m 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11m 36s\n", + "27500:\tlearn: 0.9986345\ttest: 0.9976502\tbest: 0.9976572 (26300)\ttotal: 14m 6s\tremaining: 11m 32s\n", + "27600:\tlearn: 0.9986389\ttest: 0.9976431\tbest: 0.9976572 (26300)\ttotal: 14m 11s\tremaining: 11m 30s\n", + "27700:\tlearn: 0.9986393\ttest: 0.9976502\tbest: 0.9976572 (26300)\ttotal: 14m 13s\tremaining: 11m 27s\n", + "27800:\tlearn: 0.9986420\ttest: 0.9976537\tbest: 0.9976572 (26300)\ttotal: 14m 16s\tremaining: 11m 23s\n", + "27900:\tlearn: 0.9986420\ttest: 0.9976502\tbest: 0.9976572 (26300)\ttotal: 14m 18s\tremaining: 11m 20s\n", + "28000:\tlearn: 0.9986440\ttest: 0.9976607\tbest: 0.9976607 (28000)\ttotal: 14m 22s\tremaining: 11m 17s\n", + "28100:\tlearn: 0.9986444\ttest: 0.9976643\tbest: 0.9976643 (28100)\ttotal: 14m 25s\tremaining: 11m 14s\n", + "28200:\tlearn: 0.9986487\ttest: 0.9976572\tbest: 0.9976643 (28100)\ttotal: 14m 28s\tremaining: 11m 11s\n", + "28300:\tlearn: 0.9986514\ttest: 0.9976607\tbest: 0.9976643 (28100)\ttotal: 14m 31s\tremaining: 11m 7s\n", 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"29300:\tlearn: 0.9986706\ttest: 0.9976713\tbest: 0.9976854 (29000)\ttotal: 15m 1s\tremaining: 10m 36s\n", + "29400:\tlearn: 0.9986730\ttest: 0.9976713\tbest: 0.9976854 (29000)\ttotal: 15m 5s\tremaining: 10m 34s\n", + "29500:\tlearn: 0.9986741\ttest: 0.9976678\tbest: 0.9976854 (29000)\ttotal: 15m 7s\tremaining: 10m 30s\n", + "29600:\tlearn: 0.9986765\ttest: 0.9976749\tbest: 0.9976854 (29000)\ttotal: 15m 10s\tremaining: 10m 27s\n", + "29700:\tlearn: 0.9986773\ttest: 0.9976819\tbest: 0.9976854 (29000)\ttotal: 15m 13s\tremaining: 10m 24s\n", + "29800:\tlearn: 0.9986792\ttest: 0.9976749\tbest: 0.9976854 (29000)\ttotal: 15m 17s\tremaining: 10m 21s\n", + "29900:\tlearn: 0.9986781\ttest: 0.9976749\tbest: 0.9976854 (29000)\ttotal: 15m 20s\tremaining: 10m 18s\n", + "30000:\tlearn: 0.9986812\ttest: 0.9976890\tbest: 0.9976890 (30000)\ttotal: 15m 22s\tremaining: 10m 15s\n", + "30100:\tlearn: 0.9986820\ttest: 0.9976890\tbest: 0.9976890 (30000)\ttotal: 15m 25s\tremaining: 10m 11s\n", + "30200:\tlearn: 0.9986859\ttest: 0.9976890\tbest: 0.9976890 (30000)\ttotal: 15m 29s\tremaining: 10m 9s\n", + "30300:\tlearn: 0.9986883\ttest: 0.9976854\tbest: 0.9976890 (30000)\ttotal: 15m 32s\tremaining: 10m 6s\n", + "30400:\tlearn: 0.9986910\ttest: 0.9976890\tbest: 0.9976890 (30000)\ttotal: 15m 34s\tremaining: 10m 2s\n", + "30500:\tlearn: 0.9986918\ttest: 0.9976890\tbest: 0.9976890 (30000)\ttotal: 15m 37s\tremaining: 9m 59s\n", + "30600:\tlearn: 0.9986949\ttest: 0.9976854\tbest: 0.9976890 (30000)\ttotal: 15m 40s\tremaining: 9m 56s\n", + "30700:\tlearn: 0.9986953\ttest: 0.9976890\tbest: 0.9976890 (30000)\ttotal: 15m 44s\tremaining: 9m 53s\n", + "30800:\tlearn: 0.9986957\ttest: 0.9976819\tbest: 0.9976890 (30000)\ttotal: 15m 47s\tremaining: 9m 50s\n", + "30900:\tlearn: 0.9987000\ttest: 0.9976819\tbest: 0.9976890 (30000)\ttotal: 15m 49s\tremaining: 9m 47s\n", + "31000:\tlearn: 0.9986985\ttest: 0.9976854\tbest: 0.9976890 (30000)\ttotal: 15m 52s\tremaining: 9m 43s\n", + "31100:\tlearn: 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0.9977031\tbest: 0.9977066 (31900)\ttotal: 16m 23s\tremaining: 9m 13s\n", + "32100:\tlearn: 0.9987169\ttest: 0.9976996\tbest: 0.9977066 (31900)\ttotal: 16m 26s\tremaining: 9m 9s\n", + "32200:\tlearn: 0.9987181\ttest: 0.9977066\tbest: 0.9977066 (31900)\ttotal: 16m 28s\tremaining: 9m 6s\n", + "32300:\tlearn: 0.9987228\ttest: 0.9977101\tbest: 0.9977101 (32300)\ttotal: 16m 31s\tremaining: 9m 3s\n", + "32400:\tlearn: 0.9987228\ttest: 0.9977066\tbest: 0.9977101 (32300)\ttotal: 16m 35s\tremaining: 9m\n", + "32500:\tlearn: 0.9987271\ttest: 0.9977101\tbest: 0.9977101 (32300)\ttotal: 16m 38s\tremaining: 8m 57s\n", + "32600:\tlearn: 0.9987259\ttest: 0.9977101\tbest: 0.9977101 (32300)\ttotal: 16m 41s\tremaining: 8m 54s\n", + "32700:\tlearn: 0.9987271\ttest: 0.9977031\tbest: 0.9977101 (32300)\ttotal: 16m 43s\tremaining: 8m 50s\n", + "32800:\tlearn: 0.9987282\ttest: 0.9977031\tbest: 0.9977101 (32300)\ttotal: 16m 47s\tremaining: 8m 48s\n", + "32900:\tlearn: 0.9987322\ttest: 0.9977031\tbest: 0.9977101 (32300)\ttotal: 16m 50s\tremaining: 8m 45s\n", + "33000:\tlearn: 0.9987333\ttest: 0.9977031\tbest: 0.9977101 (32300)\ttotal: 16m 53s\tremaining: 8m 41s\n", + "33100:\tlearn: 0.9987349\ttest: 0.9976996\tbest: 0.9977101 (32300)\ttotal: 16m 55s\tremaining: 8m 38s\n", + "33200:\tlearn: 0.9987361\ttest: 0.9977066\tbest: 0.9977101 (32300)\ttotal: 16m 58s\tremaining: 8m 35s\n", + "33300:\tlearn: 0.9987365\ttest: 0.9977137\tbest: 0.9977137 (33300)\ttotal: 17m 3s\tremaining: 8m 33s\n", + "33400:\tlearn: 0.9987373\ttest: 0.9977101\tbest: 0.9977137 (33300)\ttotal: 17m 5s\tremaining: 8m 29s\n", + "33500:\tlearn: 0.9987400\ttest: 0.9977066\tbest: 0.9977137 (33300)\ttotal: 17m 8s\tremaining: 8m 26s\n", + "33600:\tlearn: 0.9987400\ttest: 0.9977066\tbest: 0.9977137 (33300)\ttotal: 17m 10s\tremaining: 8m 23s\n", + "33700:\tlearn: 0.9987420\ttest: 0.9977137\tbest: 0.9977137 (33300)\ttotal: 17m 14s\tremaining: 8m 20s\n", + "33800:\tlearn: 0.9987431\ttest: 0.9977207\tbest: 0.9977207 (33800)\ttotal: 17m 17s\tremaining: 8m 17s\n", + "33900:\tlearn: 0.9987451\ttest: 0.9977207\tbest: 0.9977207 (33800)\ttotal: 17m 20s\tremaining: 8m 14s\n", + "34000:\tlearn: 0.9987443\ttest: 0.9977243\tbest: 0.9977243 (34000)\ttotal: 17m 23s\tremaining: 8m 10s\n", + "34100:\tlearn: 0.9987467\ttest: 0.9977243\tbest: 0.9977243 (34000)\ttotal: 17m 25s\tremaining: 8m 7s\n", + "34200:\tlearn: 0.9987463\ttest: 0.9977243\tbest: 0.9977243 (34000)\ttotal: 17m 30s\tremaining: 8m 5s\n", + "34300:\tlearn: 0.9987490\ttest: 0.9977278\tbest: 0.9977278 (34300)\ttotal: 17m 32s\tremaining: 8m 1s\n", + "34400:\tlearn: 0.9987510\ttest: 0.9977243\tbest: 0.9977278 (34300)\ttotal: 17m 35s\tremaining: 7m 58s\n", + "34500:\tlearn: 0.9987526\ttest: 0.9977348\tbest: 0.9977348 (34500)\ttotal: 17m 37s\tremaining: 7m 55s\n", + "34600:\tlearn: 0.9987545\ttest: 0.9977348\tbest: 0.9977348 (34500)\ttotal: 17m 42s\tremaining: 7m 52s\n", + "34700:\tlearn: 0.9987557\ttest: 0.9977348\tbest: 0.9977348 (34500)\ttotal: 17m 45s\tremaining: 7m 49s\n", + "34800:\tlearn: 0.9987584\ttest: 0.9977313\tbest: 0.9977348 (34500)\ttotal: 17m 47s\tremaining: 7m 46s\n", + "34900:\tlearn: 0.9987573\ttest: 0.9977243\tbest: 0.9977348 (34500)\ttotal: 17m 50s\tremaining: 7m 42s\n", + "35000:\tlearn: 0.9987584\ttest: 0.9977278\tbest: 0.9977348 (34500)\ttotal: 17m 53s\tremaining: 7m 40s\n", + "35100:\tlearn: 0.9987584\ttest: 0.9977313\tbest: 0.9977348 (34500)\ttotal: 17m 57s\tremaining: 7m 37s\n", + "35200:\tlearn: 0.9987608\ttest: 0.9977313\tbest: 0.9977348 (34500)\ttotal: 17m 59s\tremaining: 7m 33s\n", + "35300:\tlearn: 0.9987639\ttest: 0.9977384\tbest: 0.9977384 (35300)\ttotal: 18m 2s\tremaining: 7m 30s\n", + "35400:\tlearn: 0.9987674\ttest: 0.9977348\tbest: 0.9977384 (35300)\ttotal: 18m 5s\tremaining: 7m 27s\n", + "35500:\tlearn: 0.9987706\ttest: 0.9977348\tbest: 0.9977384 (35300)\ttotal: 18m 9s\tremaining: 7m 24s\n", + "35600:\tlearn: 0.9987714\ttest: 0.9977313\tbest: 0.9977384 (35300)\ttotal: 18m 12s\tremaining: 7m 21s\n", + "35700:\tlearn: 0.9987729\ttest: 0.9977313\tbest: 0.9977384 (35300)\ttotal: 18m 14s\tremaining: 7m 18s\n", + "35800:\tlearn: 0.9987753\ttest: 0.9977243\tbest: 0.9977384 (35300)\ttotal: 18m 17s\tremaining: 7m 15s\n", + "35900:\tlearn: 0.9987741\ttest: 0.9977243\tbest: 0.9977384 (35300)\ttotal: 18m 21s\tremaining: 7m 12s\n", + "36000:\tlearn: 0.9987737\ttest: 0.9977313\tbest: 0.9977384 (35300)\ttotal: 18m 24s\tremaining: 7m 9s\n", + "36100:\tlearn: 0.9987784\ttest: 0.9977313\tbest: 0.9977384 (35300)\ttotal: 18m 26s\tremaining: 7m 6s\n", + "36200:\tlearn: 0.9987761\ttest: 0.9977243\tbest: 0.9977384 (35300)\ttotal: 18m 29s\tremaining: 7m 2s\n", + "36300:\tlearn: 0.9987808\ttest: 0.9977313\tbest: 0.9977384 (35300)\ttotal: 18m 32s\tremaining: 6m 59s\n", + "36400:\tlearn: 0.9987765\ttest: 0.9977348\tbest: 0.9977384 (35300)\ttotal: 18m 36s\tremaining: 6m 57s\n", + "36500:\tlearn: 0.9987780\ttest: 0.9977348\tbest: 0.9977384 (35300)\ttotal: 18m 39s\tremaining: 6m 53s\n", + "36600:\tlearn: 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50000,\n", + " random_state = 69,\n", + " loss_function = \"MultiClass\",\n", + " eval_metric= 'Accuracy',\n", + " cat_features = cat_cols,\n", + " metric_period=100,\n", + " task_type = 'GPU'\n", + " )\n", + "\n", + "model.fit(X_train, y_train, plot=True, eval_set = (X_test, y_test))" + ] + }, + { + "cell_type": "code", + "source": [ + "model.get_feature_importance(prettified=True)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 519 + }, + "id": "jy8HlsPfl1U3", + "outputId": "c088c271-00d8-4206-c489-534726171752" + }, + "execution_count": 34, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " Feature Id Importances\n", + "0 Электросистема. Напряжение 24.613057\n", + "1 ДВС. Температура охлаждающей жидкости 11.264609\n", + "2 КПП. Температура масла 9.729970\n", + "3 Полож.пед.акселер.,% 9.218025\n", + "4 КПП. Давление масла в системе смазки 9.029200\n", + "5 Значение счетчика моточасов, час:мин 8.972413\n", + "6 Давление в пневмостистеме (spn46), кПа 7.963685\n", + "7 ДВС. Частота вращения коленчатого вала 5.222944\n", + "8 ДВС. Давление смазки 4.144133\n", + "9 Скорость 3.523335\n", + "10 Обор.двиг.,об/мин 3.405608\n", + "11 Давл.масла двиг.,кПа 2.508649\n", + "12 Темп.масла двиг.,°С 0.336934\n", + "13 Уровень топлива % (spn96) 0.067439\n", + "14 Сост.пед.сцепл. 0.000000" + ], + "text/html": [ + "\n", + "
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Feature IdImportances
0Электросистема. Напряжение24.613057
1ДВС. Температура охлаждающей жидкости11.264609
2КПП. Температура масла9.729970
3Полож.пед.акселер.,%9.218025
4КПП. Давление масла в системе смазки9.029200
5Значение счетчика моточасов, час:мин8.972413
6Давление в пневмостистеме (spn46), кПа7.963685
7ДВС. Частота вращения коленчатого вала5.222944
8ДВС. Давление смазки4.144133
9Скорость3.523335
10Обор.двиг.,об/мин3.405608
11Давл.масла двиг.,кПа2.508649
12Темп.масла двиг.,°С0.336934
13Уровень топлива % (spn96)0.067439
14Сост.пед.сцепл.0.000000
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