{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Evaluators Tutorial\n", "\n", "**-- On evaluation --**\n", "\n", "In this tutorial, we will cover different approaches to model evaluation. Let's start by investigating `perturb-lib` evaluators:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['MAE', 'Pearson', 'R2', 'RMSE']" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import perturb_lib as plib\n", "\n", "plib.list_evaluators()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let us focus on standard RMSE evaluator for example:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Root-mean-square error (RMSE).'" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "evaluator_id = \"RMSE\"\n", "evaluator = plib.load_evaluator(evaluator_id)\n", "plib.describe_evaluator(evaluator_id)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let us now get datasets and train a sample model." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "16:10:50 | INFO | Loading training data into RAM..\n", "16:10:51 | INFO | ReactomePathways.gmt.zip found in cache.\n", "16:10:51 | INFO | Reducing embedding to 20 dimensions using PCA.\n", "16:10:51 | INFO | Embedding training data of size 12344962..\n", "16:10:51 | INFO | Creating X matrix\n", "16:10:54 | INFO | Creating y vector\n", "16:10:54 | INFO | Fitting CatBoostRegressor on data of shape (12344962, 41)..\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "0:\tlearn: 0.1748921\ttotal: 742ms\tremaining: 12m 21s\n", "1:\tlearn: 0.1748209\ttotal: 1.06s\tremaining: 8m 50s\n", "2:\tlearn: 0.1747386\ttotal: 1.37s\tremaining: 7m 35s\n", "3:\tlearn: 0.1746807\ttotal: 1.58s\tremaining: 6m 32s\n", "4:\tlearn: 0.1745931\ttotal: 1.82s\tremaining: 6m 1s\n", "5:\tlearn: 0.1745169\ttotal: 2.06s\tremaining: 5m 42s\n", "6:\tlearn: 0.1744569\ttotal: 2.29s\tremaining: 5m 24s\n", "7:\tlearn: 0.1743925\ttotal: 2.54s\tremaining: 5m 15s\n", "8:\tlearn: 0.1743312\ttotal: 2.8s\tremaining: 5m 8s\n", "9:\tlearn: 0.1742843\ttotal: 3.06s\tremaining: 5m 2s\n", "10:\tlearn: 0.1742344\ttotal: 3.28s\tremaining: 4m 55s\n", "11:\tlearn: 0.1742010\ttotal: 3.5s\tremaining: 4m 48s\n", "12:\tlearn: 0.1741531\ttotal: 3.74s\tremaining: 4m 44s\n", "13:\tlearn: 0.1741033\ttotal: 4.01s\tremaining: 4m 42s\n", "14:\tlearn: 0.1740492\ttotal: 4.25s\tremaining: 4m 39s\n", "15:\tlearn: 0.1740027\ttotal: 4.51s\tremaining: 4m 37s\n", "16:\tlearn: 0.1739472\ttotal: 4.8s\tremaining: 4m 37s\n", "17:\tlearn: 0.1738952\ttotal: 5.09s\tremaining: 4m 37s\n", "18:\tlearn: 0.1738460\ttotal: 5.37s\tremaining: 4m 37s\n", "19:\tlearn: 0.1737908\ttotal: 5.62s\tremaining: 4m 35s\n", "20:\tlearn: 0.1737435\ttotal: 5.85s\tremaining: 4m 32s\n", "21:\tlearn: 0.1737026\ttotal: 6.09s\tremaining: 4m 30s\n", "22:\tlearn: 0.1736509\ttotal: 6.32s\tremaining: 4m 28s\n", "23:\tlearn: 0.1736177\ttotal: 6.6s\tremaining: 4m 28s\n", "24:\tlearn: 0.1735742\ttotal: 6.85s\tremaining: 4m 27s\n", "25:\tlearn: 0.1735393\ttotal: 7.06s\tremaining: 4m 24s\n", "26:\tlearn: 0.1735078\ttotal: 7.29s\tremaining: 4m 22s\n", "27:\tlearn: 0.1734702\ttotal: 7.51s\tremaining: 4m 20s\n", "28:\tlearn: 0.1734081\ttotal: 7.8s\tremaining: 4m 21s\n", "29:\tlearn: 0.1733730\ttotal: 8.05s\tremaining: 4m 20s\n", "30:\tlearn: 0.1733312\ttotal: 8.28s\tremaining: 4m 18s\n", "31:\tlearn: 0.1732966\ttotal: 8.53s\tremaining: 4m 18s\n", "32:\tlearn: 0.1732545\ttotal: 8.77s\tremaining: 4m 16s\n", "33:\tlearn: 0.1732225\ttotal: 9.01s\tremaining: 4m 15s\n", "34:\tlearn: 0.1731945\ttotal: 9.21s\tremaining: 4m 14s\n", "35:\tlearn: 0.1731647\ttotal: 9.43s\tremaining: 4m 12s\n", "36:\tlearn: 0.1731315\ttotal: 9.64s\tremaining: 4m 10s\n", "37:\tlearn: 0.1731000\ttotal: 9.89s\tremaining: 4m 10s\n", "38:\tlearn: 0.1730604\ttotal: 10.2s\tremaining: 4m 10s\n", "39:\tlearn: 0.1730288\ttotal: 10.4s\tremaining: 4m 9s\n", "40:\tlearn: 0.1729889\ttotal: 10.7s\tremaining: 4m 11s\n", "41:\tlearn: 0.1729510\ttotal: 11.2s\tremaining: 4m 14s\n", "42:\tlearn: 0.1729130\ttotal: 11.6s\tremaining: 4m 17s\n", "43:\tlearn: 0.1728892\ttotal: 11.8s\tremaining: 4m 16s\n", "44:\tlearn: 0.1728590\ttotal: 12.1s\tremaining: 4m 16s\n", "45:\tlearn: 0.1728288\ttotal: 12.3s\tremaining: 4m 15s\n", "46:\tlearn: 0.1727901\ttotal: 12.6s\tremaining: 4m 15s\n", "47:\tlearn: 0.1727701\ttotal: 12.8s\tremaining: 4m 14s\n", "48:\tlearn: 0.1727275\ttotal: 13.1s\tremaining: 4m 14s\n", "49:\tlearn: 0.1726853\ttotal: 13.4s\tremaining: 4m 14s\n", "50:\tlearn: 0.1726490\ttotal: 13.7s\tremaining: 4m 15s\n", "51:\tlearn: 0.1726215\ttotal: 13.9s\tremaining: 4m 14s\n", "52:\tlearn: 0.1725811\ttotal: 14.2s\tremaining: 4m 13s\n", "53:\tlearn: 0.1725557\ttotal: 14.5s\tremaining: 4m 13s\n", "54:\tlearn: 0.1725178\ttotal: 14.8s\tremaining: 4m 14s\n", "55:\tlearn: 0.1724945\ttotal: 15.1s\tremaining: 4m 14s\n", "56:\tlearn: 0.1724630\ttotal: 15.4s\tremaining: 4m 14s\n", "57:\tlearn: 0.1724399\ttotal: 15.7s\tremaining: 4m 14s\n", "58:\tlearn: 0.1724172\ttotal: 15.9s\tremaining: 4m 13s\n", "59:\tlearn: 0.1723790\ttotal: 16.2s\tremaining: 4m 14s\n", "60:\tlearn: 0.1723524\ttotal: 16.5s\tremaining: 4m 14s\n", "61:\tlearn: 0.1723261\ttotal: 16.8s\tremaining: 4m 13s\n", "62:\tlearn: 0.1722930\ttotal: 17.1s\tremaining: 4m 14s\n", "63:\tlearn: 0.1722617\ttotal: 17.4s\tremaining: 4m 14s\n", "64:\tlearn: 0.1722291\ttotal: 17.6s\tremaining: 4m 13s\n", "65:\tlearn: 0.1722122\ttotal: 17.9s\tremaining: 4m 12s\n", "66:\tlearn: 0.1721805\ttotal: 18.1s\tremaining: 4m 12s\n", "67:\tlearn: 0.1721587\ttotal: 18.4s\tremaining: 4m 11s\n", "68:\tlearn: 0.1721351\ttotal: 18.6s\tremaining: 4m 11s\n", "69:\tlearn: 0.1721111\ttotal: 18.9s\tremaining: 4m 11s\n", "70:\tlearn: 0.1720841\ttotal: 19.2s\tremaining: 4m 10s\n", "71:\tlearn: 0.1720553\ttotal: 19.4s\tremaining: 4m 10s\n", "72:\tlearn: 0.1720437\ttotal: 19.7s\tremaining: 4m 9s\n", "73:\tlearn: 0.1720117\ttotal: 19.9s\tremaining: 4m 9s\n", "74:\tlearn: 0.1719860\ttotal: 20.2s\tremaining: 4m 9s\n", "75:\tlearn: 0.1719729\ttotal: 20.5s\tremaining: 4m 8s\n", "76:\tlearn: 0.1719514\ttotal: 20.7s\tremaining: 4m 8s\n", "77:\tlearn: 0.1719350\ttotal: 21s\tremaining: 4m 8s\n", "78:\tlearn: 0.1719126\ttotal: 21.3s\tremaining: 4m 8s\n", "79:\tlearn: 0.1718863\ttotal: 21.6s\tremaining: 4m 8s\n", "80:\tlearn: 0.1718643\ttotal: 21.9s\tremaining: 4m 7s\n", "81:\tlearn: 0.1718407\ttotal: 22.1s\tremaining: 4m 7s\n", "82:\tlearn: 0.1718177\ttotal: 22.4s\tremaining: 4m 7s\n", "83:\tlearn: 0.1718033\ttotal: 22.7s\tremaining: 4m 7s\n", "84:\tlearn: 0.1717853\ttotal: 22.9s\tremaining: 4m 6s\n", "85:\tlearn: 0.1717661\ttotal: 23.2s\tremaining: 4m 6s\n", "86:\tlearn: 0.1717407\ttotal: 23.5s\tremaining: 4m 6s\n", "87:\tlearn: 0.1717246\ttotal: 23.7s\tremaining: 4m 6s\n", "88:\tlearn: 0.1717109\ttotal: 24s\tremaining: 4m 5s\n", "89:\tlearn: 0.1716937\ttotal: 24.3s\tremaining: 4m 5s\n", "90:\tlearn: 0.1716790\ttotal: 24.5s\tremaining: 4m 4s\n", "91:\tlearn: 0.1716599\ttotal: 24.8s\tremaining: 4m 4s\n", "92:\tlearn: 0.1716432\ttotal: 25.1s\tremaining: 4m 4s\n", "93:\tlearn: 0.1716225\ttotal: 25.4s\tremaining: 4m 4s\n", "94:\tlearn: 0.1716036\ttotal: 25.7s\tremaining: 4m 4s\n", "95:\tlearn: 0.1715846\ttotal: 26s\tremaining: 4m 4s\n", "96:\tlearn: 0.1715649\ttotal: 26.3s\tremaining: 4m 4s\n", "97:\tlearn: 0.1715512\ttotal: 26.5s\tremaining: 4m 4s\n", "98:\tlearn: 0.1715382\ttotal: 26.8s\tremaining: 4m 4s\n", "99:\tlearn: 0.1715181\ttotal: 27.1s\tremaining: 4m 4s\n", "100:\tlearn: 0.1714946\ttotal: 27.4s\tremaining: 4m 4s\n", "101:\tlearn: 0.1714789\ttotal: 27.7s\tremaining: 4m 3s\n", "102:\tlearn: 0.1714641\ttotal: 28s\tremaining: 4m 3s\n", "103:\tlearn: 0.1714524\ttotal: 28.2s\tremaining: 4m 3s\n", "104:\tlearn: 0.1714383\ttotal: 28.5s\tremaining: 4m 2s\n", "105:\tlearn: 0.1714285\ttotal: 28.7s\tremaining: 4m 2s\n", "106:\tlearn: 0.1714114\ttotal: 29s\tremaining: 4m 1s\n", "107:\tlearn: 0.1713972\ttotal: 29.2s\tremaining: 4m 1s\n", "108:\tlearn: 0.1713804\ttotal: 29.5s\tremaining: 4m\n", "109:\tlearn: 0.1713612\ttotal: 29.8s\tremaining: 4m\n", "110:\tlearn: 0.1713454\ttotal: 30s\tremaining: 4m\n", "111:\tlearn: 0.1713324\ttotal: 30.3s\tremaining: 4m\n", "112:\tlearn: 0.1713152\ttotal: 30.6s\tremaining: 4m\n", "113:\tlearn: 0.1713053\ttotal: 30.9s\tremaining: 3m 59s\n", "114:\tlearn: 0.1712846\ttotal: 31.2s\tremaining: 3m 59s\n", "115:\tlearn: 0.1712680\ttotal: 31.5s\tremaining: 3m 59s\n", "116:\tlearn: 0.1712532\ttotal: 31.8s\tremaining: 3m 59s\n", "117:\tlearn: 0.1712430\ttotal: 32s\tremaining: 3m 59s\n", "118:\tlearn: 0.1712332\ttotal: 32.3s\tremaining: 3m 58s\n", "119:\tlearn: 0.1712177\ttotal: 32.6s\tremaining: 3m 59s\n", "120:\tlearn: 0.1712057\ttotal: 32.9s\tremaining: 3m 58s\n", "121:\tlearn: 0.1711959\ttotal: 33.1s\tremaining: 3m 58s\n", "122:\tlearn: 0.1711815\ttotal: 33.5s\tremaining: 3m 58s\n", "123:\tlearn: 0.1711652\ttotal: 33.8s\tremaining: 3m 58s\n", "124:\tlearn: 0.1711515\ttotal: 34.1s\tremaining: 3m 58s\n", "125:\tlearn: 0.1711414\ttotal: 34.3s\tremaining: 3m 58s\n", "126:\tlearn: 0.1711285\ttotal: 34.7s\tremaining: 3m 58s\n", "127:\tlearn: 0.1711215\ttotal: 34.9s\tremaining: 3m 57s\n", "128:\tlearn: 0.1711108\ttotal: 35.2s\tremaining: 3m 57s\n", "129:\tlearn: 0.1710997\ttotal: 35.5s\tremaining: 3m 57s\n", "130:\tlearn: 0.1710881\ttotal: 35.8s\tremaining: 3m 57s\n", "131:\tlearn: 0.1710764\ttotal: 36s\tremaining: 3m 56s\n", "132:\tlearn: 0.1710631\ttotal: 36.3s\tremaining: 3m 56s\n", "133:\tlearn: 0.1710503\ttotal: 36.6s\tremaining: 3m 56s\n", "134:\tlearn: 0.1710377\ttotal: 37s\tremaining: 3m 56s\n", "135:\tlearn: 0.1710273\ttotal: 37.2s\tremaining: 3m 56s\n", "136:\tlearn: 0.1710177\ttotal: 37.5s\tremaining: 3m 56s\n", "137:\tlearn: 0.1710102\ttotal: 37.7s\tremaining: 3m 55s\n", "138:\tlearn: 0.1710037\ttotal: 38s\tremaining: 3m 55s\n", "139:\tlearn: 0.1709928\ttotal: 38.2s\tremaining: 3m 54s\n", "140:\tlearn: 0.1709837\ttotal: 38.5s\tremaining: 3m 54s\n", "141:\tlearn: 0.1709722\ttotal: 38.9s\tremaining: 3m 54s\n", "142:\tlearn: 0.1709567\ttotal: 39.2s\tremaining: 3m 54s\n", "143:\tlearn: 0.1709451\ttotal: 39.6s\tremaining: 3m 55s\n", "144:\tlearn: 0.1709338\ttotal: 39.9s\tremaining: 3m 55s\n", "145:\tlearn: 0.1709224\ttotal: 40.1s\tremaining: 3m 54s\n", "146:\tlearn: 0.1709112\ttotal: 40.5s\tremaining: 3m 55s\n", "147:\tlearn: 0.1709008\ttotal: 40.8s\tremaining: 3m 54s\n", "148:\tlearn: 0.1708900\ttotal: 41.1s\tremaining: 3m 54s\n", "149:\tlearn: 0.1708800\ttotal: 41.4s\tremaining: 3m 54s\n", "150:\tlearn: 0.1708708\ttotal: 41.6s\tremaining: 3m 53s\n", "151:\tlearn: 0.1708639\ttotal: 41.8s\tremaining: 3m 53s\n", "152:\tlearn: 0.1708532\ttotal: 42.1s\tremaining: 3m 53s\n", "153:\tlearn: 0.1708450\ttotal: 42.4s\tremaining: 3m 52s\n", "154:\tlearn: 0.1708352\ttotal: 42.7s\tremaining: 3m 52s\n", "155:\tlearn: 0.1708251\ttotal: 43s\tremaining: 3m 52s\n", "156:\tlearn: 0.1708174\ttotal: 43.3s\tremaining: 3m 52s\n", "157:\tlearn: 0.1708079\ttotal: 43.6s\tremaining: 3m 52s\n", "158:\tlearn: 0.1707981\ttotal: 43.9s\tremaining: 3m 52s\n", "159:\tlearn: 0.1707919\ttotal: 44.2s\tremaining: 3m 51s\n", "160:\tlearn: 0.1707870\ttotal: 44.4s\tremaining: 3m 51s\n", "161:\tlearn: 0.1707761\ttotal: 44.6s\tremaining: 3m 50s\n", "162:\tlearn: 0.1707672\ttotal: 44.9s\tremaining: 3m 50s\n", "163:\tlearn: 0.1707587\ttotal: 45.2s\tremaining: 3m 50s\n", "164:\tlearn: 0.1707529\ttotal: 45.4s\tremaining: 3m 49s\n", "165:\tlearn: 0.1707452\ttotal: 45.7s\tremaining: 3m 49s\n", "166:\tlearn: 0.1707374\ttotal: 46s\tremaining: 3m 49s\n", "167:\tlearn: 0.1707310\ttotal: 46.3s\tremaining: 3m 49s\n", "168:\tlearn: 0.1707224\ttotal: 46.6s\tremaining: 3m 48s\n", "169:\tlearn: 0.1707142\ttotal: 46.8s\tremaining: 3m 48s\n", "170:\tlearn: 0.1707064\ttotal: 47.1s\tremaining: 3m 48s\n", "171:\tlearn: 0.1706991\ttotal: 47.4s\tremaining: 3m 48s\n", "172:\tlearn: 0.1706917\ttotal: 47.6s\tremaining: 3m 47s\n", "173:\tlearn: 0.1706858\ttotal: 47.9s\tremaining: 3m 47s\n", "174:\tlearn: 0.1706794\ttotal: 48.1s\tremaining: 3m 46s\n", "175:\tlearn: 0.1706736\ttotal: 48.4s\tremaining: 3m 46s\n", "176:\tlearn: 0.1706658\ttotal: 48.6s\tremaining: 3m 46s\n", "177:\tlearn: 0.1706603\ttotal: 48.9s\tremaining: 3m 45s\n", "178:\tlearn: 0.1706530\ttotal: 49.1s\tremaining: 3m 45s\n", "179:\tlearn: 0.1706444\ttotal: 49.5s\tremaining: 3m 45s\n", "180:\tlearn: 0.1706370\ttotal: 49.8s\tremaining: 3m 45s\n", "181:\tlearn: 0.1706302\ttotal: 50.1s\tremaining: 3m 45s\n", "182:\tlearn: 0.1706223\ttotal: 50.3s\tremaining: 3m 44s\n", "183:\tlearn: 0.1706143\ttotal: 50.6s\tremaining: 3m 44s\n", "184:\tlearn: 0.1706068\ttotal: 50.9s\tremaining: 3m 44s\n", "185:\tlearn: 0.1706032\ttotal: 51.1s\tremaining: 3m 43s\n", "186:\tlearn: 0.1705972\ttotal: 51.4s\tremaining: 3m 43s\n", "187:\tlearn: 0.1705890\ttotal: 51.7s\tremaining: 3m 43s\n", "188:\tlearn: 0.1705826\ttotal: 52s\tremaining: 3m 43s\n", "189:\tlearn: 0.1705781\ttotal: 52.2s\tremaining: 3m 42s\n", "190:\tlearn: 0.1705712\ttotal: 52.5s\tremaining: 3m 42s\n", "191:\tlearn: 0.1705654\ttotal: 52.8s\tremaining: 3m 42s\n", "192:\tlearn: 0.1705609\ttotal: 53.1s\tremaining: 3m 41s\n", "193:\tlearn: 0.1705557\ttotal: 53.3s\tremaining: 3m 41s\n", "194:\tlearn: 0.1705497\ttotal: 53.6s\tremaining: 3m 41s\n", "195:\tlearn: 0.1705456\ttotal: 53.8s\tremaining: 3m 40s\n", "196:\tlearn: 0.1705399\ttotal: 54.1s\tremaining: 3m 40s\n", "197:\tlearn: 0.1705350\ttotal: 54.3s\tremaining: 3m 40s\n", "198:\tlearn: 0.1705285\ttotal: 54.7s\tremaining: 3m 40s\n", "199:\tlearn: 0.1705234\ttotal: 55s\tremaining: 3m 40s\n", "200:\tlearn: 0.1705178\ttotal: 55.3s\tremaining: 3m 39s\n", "201:\tlearn: 0.1705099\ttotal: 55.6s\tremaining: 3m 39s\n", "202:\tlearn: 0.1705042\ttotal: 55.9s\tremaining: 3m 39s\n", "203:\tlearn: 0.1704973\ttotal: 56.2s\tremaining: 3m 39s\n", "204:\tlearn: 0.1704919\ttotal: 56.4s\tremaining: 3m 38s\n", "205:\tlearn: 0.1704860\ttotal: 56.7s\tremaining: 3m 38s\n", "206:\tlearn: 0.1704807\ttotal: 57s\tremaining: 3m 38s\n", "207:\tlearn: 0.1704735\ttotal: 57.3s\tremaining: 3m 38s\n", "208:\tlearn: 0.1704676\ttotal: 57.6s\tremaining: 3m 37s\n", "209:\tlearn: 0.1704617\ttotal: 57.9s\tremaining: 3m 37s\n", "210:\tlearn: 0.1704576\ttotal: 58.1s\tremaining: 3m 37s\n", "211:\tlearn: 0.1704521\ttotal: 58.4s\tremaining: 3m 37s\n", "212:\tlearn: 0.1704480\ttotal: 58.7s\tremaining: 3m 36s\n", "213:\tlearn: 0.1704422\ttotal: 58.9s\tremaining: 3m 36s\n", "214:\tlearn: 0.1704378\ttotal: 59.2s\tremaining: 3m 36s\n", "215:\tlearn: 0.1704322\ttotal: 59.5s\tremaining: 3m 35s\n", "216:\tlearn: 0.1704268\ttotal: 59.8s\tremaining: 3m 35s\n", "217:\tlearn: 0.1704204\ttotal: 1m\tremaining: 3m 35s\n", "218:\tlearn: 0.1704142\ttotal: 1m\tremaining: 3m 35s\n", "219:\tlearn: 0.1704100\ttotal: 1m\tremaining: 3m 34s\n", "220:\tlearn: 0.1704037\ttotal: 1m\tremaining: 3m 34s\n", "221:\tlearn: 0.1703982\ttotal: 1m 1s\tremaining: 3m 34s\n", "222:\tlearn: 0.1703946\ttotal: 1m 1s\tremaining: 3m 34s\n", "223:\tlearn: 0.1703882\ttotal: 1m 1s\tremaining: 3m 34s\n", "224:\tlearn: 0.1703833\ttotal: 1m 2s\tremaining: 3m 33s\n", "225:\tlearn: 0.1703791\ttotal: 1m 2s\tremaining: 3m 33s\n", "226:\tlearn: 0.1703740\ttotal: 1m 2s\tremaining: 3m 33s\n", "227:\tlearn: 0.1703703\ttotal: 1m 3s\tremaining: 3m 33s\n", "228:\tlearn: 0.1703657\ttotal: 1m 3s\tremaining: 3m 33s\n", "229:\tlearn: 0.1703617\ttotal: 1m 3s\tremaining: 3m 33s\n", "230:\tlearn: 0.1703580\ttotal: 1m 3s\tremaining: 3m 32s\n", "231:\tlearn: 0.1703556\ttotal: 1m 4s\tremaining: 3m 32s\n", "232:\tlearn: 0.1703492\ttotal: 1m 4s\tremaining: 3m 32s\n", "233:\tlearn: 0.1703451\ttotal: 1m 4s\tremaining: 3m 31s\n", "234:\tlearn: 0.1703419\ttotal: 1m 4s\tremaining: 3m 31s\n", "235:\tlearn: 0.1703374\ttotal: 1m 5s\tremaining: 3m 31s\n", "236:\tlearn: 0.1703327\ttotal: 1m 5s\tremaining: 3m 31s\n", "237:\tlearn: 0.1703280\ttotal: 1m 5s\tremaining: 3m 30s\n", "238:\tlearn: 0.1703252\ttotal: 1m 6s\tremaining: 3m 30s\n", "239:\tlearn: 0.1703213\ttotal: 1m 6s\tremaining: 3m 30s\n", "240:\tlearn: 0.1703181\ttotal: 1m 6s\tremaining: 3m 29s\n", "241:\tlearn: 0.1703145\ttotal: 1m 6s\tremaining: 3m 29s\n", "242:\tlearn: 0.1703094\ttotal: 1m 7s\tremaining: 3m 29s\n", "243:\tlearn: 0.1703064\ttotal: 1m 7s\tremaining: 3m 28s\n", "244:\tlearn: 0.1703035\ttotal: 1m 7s\tremaining: 3m 28s\n", "245:\tlearn: 0.1702995\ttotal: 1m 7s\tremaining: 3m 28s\n", "246:\tlearn: 0.1702939\ttotal: 1m 8s\tremaining: 3m 28s\n", "247:\tlearn: 0.1702908\ttotal: 1m 8s\tremaining: 3m 27s\n", "248:\tlearn: 0.1702856\ttotal: 1m 8s\tremaining: 3m 27s\n", "249:\tlearn: 0.1702809\ttotal: 1m 9s\tremaining: 3m 27s\n", "250:\tlearn: 0.1702782\ttotal: 1m 9s\tremaining: 3m 26s\n", "251:\tlearn: 0.1702757\ttotal: 1m 9s\tremaining: 3m 26s\n", "252:\tlearn: 0.1702719\ttotal: 1m 9s\tremaining: 3m 26s\n", "253:\tlearn: 0.1702688\ttotal: 1m 10s\tremaining: 3m 25s\n", "254:\tlearn: 0.1702664\ttotal: 1m 10s\tremaining: 3m 25s\n", "255:\tlearn: 0.1702626\ttotal: 1m 10s\tremaining: 3m 25s\n", "256:\tlearn: 0.1702597\ttotal: 1m 10s\tremaining: 3m 24s\n", "257:\tlearn: 0.1702561\ttotal: 1m 11s\tremaining: 3m 24s\n", "258:\tlearn: 0.1702528\ttotal: 1m 11s\tremaining: 3m 24s\n", "259:\tlearn: 0.1702496\ttotal: 1m 11s\tremaining: 3m 24s\n", "260:\tlearn: 0.1702464\ttotal: 1m 11s\tremaining: 3m 23s\n", "261:\tlearn: 0.1702427\ttotal: 1m 12s\tremaining: 3m 23s\n", "262:\tlearn: 0.1702396\ttotal: 1m 12s\tremaining: 3m 23s\n", "263:\tlearn: 0.1702364\ttotal: 1m 12s\tremaining: 3m 22s\n", "264:\tlearn: 0.1702332\ttotal: 1m 12s\tremaining: 3m 22s\n", "265:\tlearn: 0.1702300\ttotal: 1m 13s\tremaining: 3m 22s\n", "266:\tlearn: 0.1702262\ttotal: 1m 13s\tremaining: 3m 21s\n", "267:\tlearn: 0.1702230\ttotal: 1m 13s\tremaining: 3m 21s\n", "268:\tlearn: 0.1702202\ttotal: 1m 14s\tremaining: 3m 21s\n", "269:\tlearn: 0.1702164\ttotal: 1m 14s\tremaining: 3m 21s\n", "270:\tlearn: 0.1702146\ttotal: 1m 14s\tremaining: 3m 20s\n", "271:\tlearn: 0.1702106\ttotal: 1m 14s\tremaining: 3m 20s\n", "272:\tlearn: 0.1702070\ttotal: 1m 15s\tremaining: 3m 20s\n", "273:\tlearn: 0.1702039\ttotal: 1m 15s\tremaining: 3m 19s\n", "274:\tlearn: 0.1702019\ttotal: 1m 15s\tremaining: 3m 19s\n", "275:\tlearn: 0.1701985\ttotal: 1m 15s\tremaining: 3m 19s\n", "276:\tlearn: 0.1701957\ttotal: 1m 16s\tremaining: 3m 19s\n", "277:\tlearn: 0.1701938\ttotal: 1m 16s\tremaining: 3m 18s\n", "278:\tlearn: 0.1701909\ttotal: 1m 16s\tremaining: 3m 18s\n", "279:\tlearn: 0.1701888\ttotal: 1m 17s\tremaining: 3m 18s\n", "280:\tlearn: 0.1701870\ttotal: 1m 17s\tremaining: 3m 17s\n", "281:\tlearn: 0.1701845\ttotal: 1m 17s\tremaining: 3m 17s\n", "282:\tlearn: 0.1701813\ttotal: 1m 17s\tremaining: 3m 17s\n", "283:\tlearn: 0.1701785\ttotal: 1m 18s\tremaining: 3m 16s\n", "284:\tlearn: 0.1701754\ttotal: 1m 18s\tremaining: 3m 16s\n", "285:\tlearn: 0.1701734\ttotal: 1m 18s\tremaining: 3m 16s\n", "286:\tlearn: 0.1701703\ttotal: 1m 18s\tremaining: 3m 16s\n", "287:\tlearn: 0.1701683\ttotal: 1m 19s\tremaining: 3m 15s\n", "288:\tlearn: 0.1701663\ttotal: 1m 19s\tremaining: 3m 15s\n", "289:\tlearn: 0.1701640\ttotal: 1m 19s\tremaining: 3m 15s\n", "290:\tlearn: 0.1701604\ttotal: 1m 20s\tremaining: 3m 15s\n", "291:\tlearn: 0.1701587\ttotal: 1m 20s\tremaining: 3m 14s\n", "292:\tlearn: 0.1701558\ttotal: 1m 20s\tremaining: 3m 14s\n", "293:\tlearn: 0.1701537\ttotal: 1m 20s\tremaining: 3m 14s\n", "294:\tlearn: 0.1701520\ttotal: 1m 21s\tremaining: 3m 13s\n", "295:\tlearn: 0.1701496\ttotal: 1m 21s\tremaining: 3m 13s\n", "296:\tlearn: 0.1701479\ttotal: 1m 21s\tremaining: 3m 13s\n", "297:\tlearn: 0.1701457\ttotal: 1m 21s\tremaining: 3m 12s\n", "298:\tlearn: 0.1701438\ttotal: 1m 22s\tremaining: 3m 12s\n", "299:\tlearn: 0.1701413\ttotal: 1m 22s\tremaining: 3m 12s\n", "300:\tlearn: 0.1701384\ttotal: 1m 22s\tremaining: 3m 11s\n", "301:\tlearn: 0.1701361\ttotal: 1m 22s\tremaining: 3m 11s\n", "302:\tlearn: 0.1701346\ttotal: 1m 23s\tremaining: 3m 11s\n", "303:\tlearn: 0.1701317\ttotal: 1m 23s\tremaining: 3m 11s\n", "304:\tlearn: 0.1701295\ttotal: 1m 23s\tremaining: 3m 10s\n", "305:\tlearn: 0.1701276\ttotal: 1m 23s\tremaining: 3m 10s\n", "306:\tlearn: 0.1701246\ttotal: 1m 24s\tremaining: 3m 10s\n", "307:\tlearn: 0.1701231\ttotal: 1m 24s\tremaining: 3m 9s\n", "308:\tlearn: 0.1701210\ttotal: 1m 24s\tremaining: 3m 9s\n", "309:\tlearn: 0.1701186\ttotal: 1m 24s\tremaining: 3m 9s\n", "310:\tlearn: 0.1701165\ttotal: 1m 25s\tremaining: 3m 8s\n", "311:\tlearn: 0.1701145\ttotal: 1m 25s\tremaining: 3m 8s\n", "312:\tlearn: 0.1701122\ttotal: 1m 25s\tremaining: 3m 8s\n", "313:\tlearn: 0.1701101\ttotal: 1m 26s\tremaining: 3m 8s\n", "314:\tlearn: 0.1701082\ttotal: 1m 26s\tremaining: 3m 7s\n", "315:\tlearn: 0.1701062\ttotal: 1m 26s\tremaining: 3m 7s\n", "316:\tlearn: 0.1701045\ttotal: 1m 26s\tremaining: 3m 7s\n", "317:\tlearn: 0.1701021\ttotal: 1m 27s\tremaining: 3m 6s\n", "318:\tlearn: 0.1701003\ttotal: 1m 27s\tremaining: 3m 6s\n", "319:\tlearn: 0.1700991\ttotal: 1m 27s\tremaining: 3m 6s\n", "320:\tlearn: 0.1700973\ttotal: 1m 27s\tremaining: 3m 5s\n", "321:\tlearn: 0.1700958\ttotal: 1m 28s\tremaining: 3m 5s\n", "322:\tlearn: 0.1700933\ttotal: 1m 28s\tremaining: 3m 5s\n", "323:\tlearn: 0.1700916\ttotal: 1m 28s\tremaining: 3m 5s\n", "324:\tlearn: 0.1700899\ttotal: 1m 29s\tremaining: 3m 4s\n", "325:\tlearn: 0.1700879\ttotal: 1m 29s\tremaining: 3m 4s\n", "326:\tlearn: 0.1700862\ttotal: 1m 29s\tremaining: 3m 4s\n", "327:\tlearn: 0.1700838\ttotal: 1m 29s\tremaining: 3m 4s\n", "328:\tlearn: 0.1700822\ttotal: 1m 30s\tremaining: 3m 3s\n", "329:\tlearn: 0.1700806\ttotal: 1m 30s\tremaining: 3m 3s\n", "330:\tlearn: 0.1700788\ttotal: 1m 30s\tremaining: 3m 3s\n", "331:\tlearn: 0.1700773\ttotal: 1m 30s\tremaining: 3m 2s\n", "332:\tlearn: 0.1700762\ttotal: 1m 31s\tremaining: 3m 2s\n", "333:\tlearn: 0.1700746\ttotal: 1m 31s\tremaining: 3m 2s\n", "334:\tlearn: 0.1700727\ttotal: 1m 31s\tremaining: 3m 2s\n", "335:\tlearn: 0.1700714\ttotal: 1m 31s\tremaining: 3m 1s\n", "336:\tlearn: 0.1700698\ttotal: 1m 32s\tremaining: 3m 1s\n", "337:\tlearn: 0.1700679\ttotal: 1m 32s\tremaining: 3m 1s\n", "338:\tlearn: 0.1700666\ttotal: 1m 32s\tremaining: 3m\n", "339:\tlearn: 0.1700649\ttotal: 1m 32s\tremaining: 3m\n", "340:\tlearn: 0.1700633\ttotal: 1m 33s\tremaining: 3m\n", "341:\tlearn: 0.1700617\ttotal: 1m 33s\tremaining: 2m 59s\n", "342:\tlearn: 0.1700595\ttotal: 1m 33s\tremaining: 2m 59s\n", "343:\tlearn: 0.1700583\ttotal: 1m 34s\tremaining: 2m 59s\n", "344:\tlearn: 0.1700566\ttotal: 1m 34s\tremaining: 2m 59s\n", "345:\tlearn: 0.1700553\ttotal: 1m 34s\tremaining: 2m 58s\n", "346:\tlearn: 0.1700535\ttotal: 1m 34s\tremaining: 2m 58s\n", "347:\tlearn: 0.1700519\ttotal: 1m 35s\tremaining: 2m 58s\n", "348:\tlearn: 0.1700503\ttotal: 1m 35s\tremaining: 2m 57s\n", "349:\tlearn: 0.1700483\ttotal: 1m 35s\tremaining: 2m 57s\n", "350:\tlearn: 0.1700465\ttotal: 1m 36s\tremaining: 2m 57s\n", "351:\tlearn: 0.1700448\ttotal: 1m 36s\tremaining: 2m 57s\n", "352:\tlearn: 0.1700429\ttotal: 1m 36s\tremaining: 2m 57s\n", "353:\tlearn: 0.1700415\ttotal: 1m 37s\tremaining: 2m 57s\n", "354:\tlearn: 0.1700400\ttotal: 1m 37s\tremaining: 2m 56s\n", "355:\tlearn: 0.1700389\ttotal: 1m 37s\tremaining: 2m 56s\n", "356:\tlearn: 0.1700369\ttotal: 1m 37s\tremaining: 2m 56s\n", "357:\tlearn: 0.1700354\ttotal: 1m 38s\tremaining: 2m 56s\n", "358:\tlearn: 0.1700337\ttotal: 1m 38s\tremaining: 2m 55s\n", "359:\tlearn: 0.1700321\ttotal: 1m 38s\tremaining: 2m 55s\n", "360:\tlearn: 0.1700310\ttotal: 1m 38s\tremaining: 2m 55s\n", "361:\tlearn: 0.1700294\ttotal: 1m 39s\tremaining: 2m 54s\n", "362:\tlearn: 0.1700282\ttotal: 1m 39s\tremaining: 2m 54s\n", "363:\tlearn: 0.1700266\ttotal: 1m 39s\tremaining: 2m 54s\n", "364:\tlearn: 0.1700256\ttotal: 1m 40s\tremaining: 2m 54s\n", "365:\tlearn: 0.1700242\ttotal: 1m 40s\tremaining: 2m 53s\n", "366:\tlearn: 0.1700233\ttotal: 1m 40s\tremaining: 2m 53s\n", "367:\tlearn: 0.1700215\ttotal: 1m 40s\tremaining: 2m 53s\n", "368:\tlearn: 0.1700198\ttotal: 1m 41s\tremaining: 2m 53s\n", "369:\tlearn: 0.1700180\ttotal: 1m 41s\tremaining: 2m 52s\n", "370:\tlearn: 0.1700163\ttotal: 1m 41s\tremaining: 2m 52s\n", "371:\tlearn: 0.1700152\ttotal: 1m 42s\tremaining: 2m 52s\n", "372:\tlearn: 0.1700141\ttotal: 1m 42s\tremaining: 2m 52s\n", "373:\tlearn: 0.1700132\ttotal: 1m 42s\tremaining: 2m 51s\n", "374:\tlearn: 0.1700116\ttotal: 1m 42s\tremaining: 2m 51s\n", "375:\tlearn: 0.1700106\ttotal: 1m 43s\tremaining: 2m 51s\n", "376:\tlearn: 0.1700100\ttotal: 1m 43s\tremaining: 2m 50s\n", "377:\tlearn: 0.1700090\ttotal: 1m 43s\tremaining: 2m 50s\n", "378:\tlearn: 0.1700077\ttotal: 1m 43s\tremaining: 2m 50s\n", "379:\tlearn: 0.1700071\ttotal: 1m 44s\tremaining: 2m 49s\n", "380:\tlearn: 0.1700055\ttotal: 1m 44s\tremaining: 2m 49s\n", "381:\tlearn: 0.1700045\ttotal: 1m 44s\tremaining: 2m 49s\n", "382:\tlearn: 0.1700034\ttotal: 1m 45s\tremaining: 2m 49s\n", "383:\tlearn: 0.1700021\ttotal: 1m 45s\tremaining: 2m 49s\n", "384:\tlearn: 0.1700009\ttotal: 1m 45s\tremaining: 2m 48s\n", "385:\tlearn: 0.1699995\ttotal: 1m 45s\tremaining: 2m 48s\n", "386:\tlearn: 0.1699984\ttotal: 1m 46s\tremaining: 2m 48s\n", "387:\tlearn: 0.1699972\ttotal: 1m 46s\tremaining: 2m 47s\n", "388:\tlearn: 0.1699958\ttotal: 1m 46s\tremaining: 2m 47s\n", "389:\tlearn: 0.1699943\ttotal: 1m 47s\tremaining: 2m 47s\n", "390:\tlearn: 0.1699937\ttotal: 1m 47s\tremaining: 2m 47s\n", "391:\tlearn: 0.1699926\ttotal: 1m 47s\tremaining: 2m 47s\n", "392:\tlearn: 0.1699915\ttotal: 1m 47s\tremaining: 2m 46s\n", "393:\tlearn: 0.1699903\ttotal: 1m 48s\tremaining: 2m 46s\n", "394:\tlearn: 0.1699891\ttotal: 1m 48s\tremaining: 2m 46s\n", "395:\tlearn: 0.1699879\ttotal: 1m 48s\tremaining: 2m 46s\n", "396:\tlearn: 0.1699871\ttotal: 1m 49s\tremaining: 2m 45s\n", "397:\tlearn: 0.1699862\ttotal: 1m 49s\tremaining: 2m 45s\n", "398:\tlearn: 0.1699851\ttotal: 1m 49s\tremaining: 2m 45s\n", "399:\tlearn: 0.1699846\ttotal: 1m 49s\tremaining: 2m 44s\n", "400:\tlearn: 0.1699839\ttotal: 1m 50s\tremaining: 2m 44s\n", "401:\tlearn: 0.1699827\ttotal: 1m 50s\tremaining: 2m 44s\n", "402:\tlearn: 0.1699817\ttotal: 1m 50s\tremaining: 2m 44s\n", "403:\tlearn: 0.1699810\ttotal: 1m 51s\tremaining: 2m 43s\n", "404:\tlearn: 0.1699795\ttotal: 1m 51s\tremaining: 2m 43s\n", "405:\tlearn: 0.1699781\ttotal: 1m 51s\tremaining: 2m 43s\n", "406:\tlearn: 0.1699771\ttotal: 1m 52s\tremaining: 2m 43s\n", "407:\tlearn: 0.1699762\ttotal: 1m 52s\tremaining: 2m 43s\n", "408:\tlearn: 0.1699752\ttotal: 1m 52s\tremaining: 2m 42s\n", "409:\tlearn: 0.1699743\ttotal: 1m 53s\tremaining: 2m 42s\n", "410:\tlearn: 0.1699737\ttotal: 1m 53s\tremaining: 2m 42s\n", "411:\tlearn: 0.1699728\ttotal: 1m 53s\tremaining: 2m 42s\n", "412:\tlearn: 0.1699717\ttotal: 1m 53s\tremaining: 2m 41s\n", "413:\tlearn: 0.1699709\ttotal: 1m 54s\tremaining: 2m 41s\n", "414:\tlearn: 0.1699702\ttotal: 1m 54s\tremaining: 2m 41s\n", "415:\tlearn: 0.1699691\ttotal: 1m 54s\tremaining: 2m 41s\n", "416:\tlearn: 0.1699681\ttotal: 1m 55s\tremaining: 2m 40s\n", "417:\tlearn: 0.1699671\ttotal: 1m 55s\tremaining: 2m 40s\n", "418:\tlearn: 0.1699661\ttotal: 1m 55s\tremaining: 2m 40s\n", "419:\tlearn: 0.1699655\ttotal: 1m 55s\tremaining: 2m 40s\n", "420:\tlearn: 0.1699646\ttotal: 1m 56s\tremaining: 2m 39s\n", "421:\tlearn: 0.1699640\ttotal: 1m 56s\tremaining: 2m 39s\n", "422:\tlearn: 0.1699630\ttotal: 1m 56s\tremaining: 2m 39s\n", "423:\tlearn: 0.1699622\ttotal: 1m 57s\tremaining: 2m 39s\n", "424:\tlearn: 0.1699610\ttotal: 1m 57s\tremaining: 2m 39s\n", "425:\tlearn: 0.1699603\ttotal: 1m 57s\tremaining: 2m 38s\n", "426:\tlearn: 0.1699595\ttotal: 1m 58s\tremaining: 2m 38s\n", "427:\tlearn: 0.1699588\ttotal: 1m 58s\tremaining: 2m 38s\n", "428:\tlearn: 0.1699579\ttotal: 1m 58s\tremaining: 2m 38s\n", "429:\tlearn: 0.1699570\ttotal: 1m 59s\tremaining: 2m 37s\n", "430:\tlearn: 0.1699564\ttotal: 1m 59s\tremaining: 2m 37s\n", "431:\tlearn: 0.1699557\ttotal: 1m 59s\tremaining: 2m 37s\n", "432:\tlearn: 0.1699550\ttotal: 1m 59s\tremaining: 2m 36s\n", "433:\tlearn: 0.1699545\ttotal: 2m\tremaining: 2m 36s\n", "434:\tlearn: 0.1699537\ttotal: 2m\tremaining: 2m 36s\n", "435:\tlearn: 0.1699530\ttotal: 2m\tremaining: 2m 36s\n", "436:\tlearn: 0.1699524\ttotal: 2m 1s\tremaining: 2m 35s\n", "437:\tlearn: 0.1699516\ttotal: 2m 1s\tremaining: 2m 35s\n", "438:\tlearn: 0.1699510\ttotal: 2m 1s\tremaining: 2m 35s\n", "439:\tlearn: 0.1699504\ttotal: 2m 1s\tremaining: 2m 35s\n", "440:\tlearn: 0.1699498\ttotal: 2m 2s\tremaining: 2m 34s\n", "441:\tlearn: 0.1699492\ttotal: 2m 2s\tremaining: 2m 34s\n", "442:\tlearn: 0.1699486\ttotal: 2m 2s\tremaining: 2m 34s\n", "443:\tlearn: 0.1699480\ttotal: 2m 3s\tremaining: 2m 34s\n", "444:\tlearn: 0.1699473\ttotal: 2m 3s\tremaining: 2m 33s\n", "445:\tlearn: 0.1699468\ttotal: 2m 3s\tremaining: 2m 33s\n", "446:\tlearn: 0.1699463\ttotal: 2m 3s\tremaining: 2m 33s\n", "447:\tlearn: 0.1699458\ttotal: 2m 4s\tremaining: 2m 33s\n", "448:\tlearn: 0.1699453\ttotal: 2m 4s\tremaining: 2m 32s\n", "449:\tlearn: 0.1699449\ttotal: 2m 4s\tremaining: 2m 32s\n", "450:\tlearn: 0.1699444\ttotal: 2m 4s\tremaining: 2m 32s\n", "451:\tlearn: 0.1699437\ttotal: 2m 5s\tremaining: 2m 31s\n", "452:\tlearn: 0.1699430\ttotal: 2m 5s\tremaining: 2m 31s\n", "453:\tlearn: 0.1699423\ttotal: 2m 5s\tremaining: 2m 31s\n", "454:\tlearn: 0.1699417\ttotal: 2m 6s\tremaining: 2m 31s\n", "455:\tlearn: 0.1699410\ttotal: 2m 6s\tremaining: 2m 31s\n", "456:\tlearn: 0.1699403\ttotal: 2m 6s\tremaining: 2m 30s\n", "457:\tlearn: 0.1699400\ttotal: 2m 7s\tremaining: 2m 30s\n", "458:\tlearn: 0.1699395\ttotal: 2m 7s\tremaining: 2m 30s\n", "459:\tlearn: 0.1699390\ttotal: 2m 7s\tremaining: 2m 29s\n", "460:\tlearn: 0.1699386\ttotal: 2m 7s\tremaining: 2m 29s\n", "461:\tlearn: 0.1699380\ttotal: 2m 8s\tremaining: 2m 29s\n", "462:\tlearn: 0.1699373\ttotal: 2m 8s\tremaining: 2m 29s\n", "463:\tlearn: 0.1699366\ttotal: 2m 8s\tremaining: 2m 28s\n", "464:\tlearn: 0.1699361\ttotal: 2m 9s\tremaining: 2m 28s\n", "465:\tlearn: 0.1699355\ttotal: 2m 9s\tremaining: 2m 28s\n", "466:\tlearn: 0.1699350\ttotal: 2m 9s\tremaining: 2m 28s\n", "467:\tlearn: 0.1699345\ttotal: 2m 9s\tremaining: 2m 27s\n", "468:\tlearn: 0.1699340\ttotal: 2m 10s\tremaining: 2m 27s\n", "469:\tlearn: 0.1699332\ttotal: 2m 10s\tremaining: 2m 27s\n", "470:\tlearn: 0.1699325\ttotal: 2m 10s\tremaining: 2m 26s\n", "471:\tlearn: 0.1699317\ttotal: 2m 11s\tremaining: 2m 26s\n", "472:\tlearn: 0.1699313\ttotal: 2m 11s\tremaining: 2m 26s\n", "473:\tlearn: 0.1699309\ttotal: 2m 11s\tremaining: 2m 26s\n", "474:\tlearn: 0.1699302\ttotal: 2m 11s\tremaining: 2m 25s\n", "475:\tlearn: 0.1699298\ttotal: 2m 12s\tremaining: 2m 25s\n", "476:\tlearn: 0.1699294\ttotal: 2m 12s\tremaining: 2m 25s\n", "477:\tlearn: 0.1699289\ttotal: 2m 12s\tremaining: 2m 24s\n", "478:\tlearn: 0.1699286\ttotal: 2m 13s\tremaining: 2m 24s\n", "479:\tlearn: 0.1699282\ttotal: 2m 13s\tremaining: 2m 24s\n", "480:\tlearn: 0.1699276\ttotal: 2m 13s\tremaining: 2m 24s\n", "481:\tlearn: 0.1699272\ttotal: 2m 13s\tremaining: 2m 23s\n", "482:\tlearn: 0.1699265\ttotal: 2m 14s\tremaining: 2m 23s\n", "483:\tlearn: 0.1699259\ttotal: 2m 14s\tremaining: 2m 23s\n", "484:\tlearn: 0.1699252\ttotal: 2m 14s\tremaining: 2m 23s\n", "485:\tlearn: 0.1699248\ttotal: 2m 15s\tremaining: 2m 22s\n", "486:\tlearn: 0.1699243\ttotal: 2m 15s\tremaining: 2m 22s\n", "487:\tlearn: 0.1699239\ttotal: 2m 15s\tremaining: 2m 22s\n", "488:\tlearn: 0.1699235\ttotal: 2m 15s\tremaining: 2m 22s\n", "489:\tlearn: 0.1699232\ttotal: 2m 16s\tremaining: 2m 21s\n", "490:\tlearn: 0.1699227\ttotal: 2m 16s\tremaining: 2m 21s\n", "491:\tlearn: 0.1699222\ttotal: 2m 16s\tremaining: 2m 21s\n", "492:\tlearn: 0.1699219\ttotal: 2m 16s\tremaining: 2m 20s\n", "493:\tlearn: 0.1699216\ttotal: 2m 17s\tremaining: 2m 20s\n", "494:\tlearn: 0.1699213\ttotal: 2m 17s\tremaining: 2m 20s\n", "495:\tlearn: 0.1699206\ttotal: 2m 17s\tremaining: 2m 20s\n", "496:\tlearn: 0.1699201\ttotal: 2m 18s\tremaining: 2m 19s\n", "497:\tlearn: 0.1699198\ttotal: 2m 18s\tremaining: 2m 19s\n", "498:\tlearn: 0.1699193\ttotal: 2m 18s\tremaining: 2m 19s\n", "499:\tlearn: 0.1699189\ttotal: 2m 18s\tremaining: 2m 18s\n", "500:\tlearn: 0.1699185\ttotal: 2m 19s\tremaining: 2m 18s\n", "501:\tlearn: 0.1699181\ttotal: 2m 19s\tremaining: 2m 18s\n", "502:\tlearn: 0.1699178\ttotal: 2m 19s\tremaining: 2m 18s\n", "503:\tlearn: 0.1699175\ttotal: 2m 19s\tremaining: 2m 17s\n", "504:\tlearn: 0.1699172\ttotal: 2m 20s\tremaining: 2m 17s\n", "505:\tlearn: 0.1699167\ttotal: 2m 20s\tremaining: 2m 17s\n", "506:\tlearn: 0.1699162\ttotal: 2m 20s\tremaining: 2m 16s\n", "507:\tlearn: 0.1699158\ttotal: 2m 21s\tremaining: 2m 16s\n", "508:\tlearn: 0.1699156\ttotal: 2m 21s\tremaining: 2m 16s\n", "509:\tlearn: 0.1699152\ttotal: 2m 21s\tremaining: 2m 16s\n", "510:\tlearn: 0.1699149\ttotal: 2m 21s\tremaining: 2m 15s\n", "511:\tlearn: 0.1699145\ttotal: 2m 22s\tremaining: 2m 15s\n", "512:\tlearn: 0.1699142\ttotal: 2m 22s\tremaining: 2m 15s\n", "513:\tlearn: 0.1699138\ttotal: 2m 22s\tremaining: 2m 14s\n", "514:\tlearn: 0.1699134\ttotal: 2m 22s\tremaining: 2m 14s\n", "515:\tlearn: 0.1699129\ttotal: 2m 23s\tremaining: 2m 14s\n", "516:\tlearn: 0.1699126\ttotal: 2m 23s\tremaining: 2m 14s\n", "517:\tlearn: 0.1699122\ttotal: 2m 23s\tremaining: 2m 13s\n", "518:\tlearn: 0.1699119\ttotal: 2m 24s\tremaining: 2m 13s\n", "519:\tlearn: 0.1699116\ttotal: 2m 24s\tremaining: 2m 13s\n", "520:\tlearn: 0.1699112\ttotal: 2m 24s\tremaining: 2m 12s\n", "521:\tlearn: 0.1699109\ttotal: 2m 24s\tremaining: 2m 12s\n", "522:\tlearn: 0.1699106\ttotal: 2m 25s\tremaining: 2m 12s\n", "523:\tlearn: 0.1699102\ttotal: 2m 25s\tremaining: 2m 12s\n", "524:\tlearn: 0.1699099\ttotal: 2m 25s\tremaining: 2m 11s\n", "525:\tlearn: 0.1699094\ttotal: 2m 26s\tremaining: 2m 11s\n", "526:\tlearn: 0.1699092\ttotal: 2m 26s\tremaining: 2m 11s\n", "527:\tlearn: 0.1699089\ttotal: 2m 26s\tremaining: 2m 10s\n", "528:\tlearn: 0.1699085\ttotal: 2m 26s\tremaining: 2m 10s\n", "529:\tlearn: 0.1699083\ttotal: 2m 27s\tremaining: 2m 10s\n", "530:\tlearn: 0.1699079\ttotal: 2m 27s\tremaining: 2m 10s\n", "531:\tlearn: 0.1699076\ttotal: 2m 27s\tremaining: 2m 9s\n", "532:\tlearn: 0.1699074\ttotal: 2m 27s\tremaining: 2m 9s\n", "533:\tlearn: 0.1699070\ttotal: 2m 28s\tremaining: 2m 9s\n", "534:\tlearn: 0.1699066\ttotal: 2m 28s\tremaining: 2m 9s\n", "535:\tlearn: 0.1699063\ttotal: 2m 28s\tremaining: 2m 8s\n", "536:\tlearn: 0.1699061\ttotal: 2m 28s\tremaining: 2m 8s\n", "537:\tlearn: 0.1699058\ttotal: 2m 29s\tremaining: 2m 8s\n", "538:\tlearn: 0.1699057\ttotal: 2m 29s\tremaining: 2m 7s\n", "539:\tlearn: 0.1699054\ttotal: 2m 29s\tremaining: 2m 7s\n", "540:\tlearn: 0.1699050\ttotal: 2m 29s\tremaining: 2m 7s\n", "541:\tlearn: 0.1699047\ttotal: 2m 30s\tremaining: 2m 6s\n", "542:\tlearn: 0.1699043\ttotal: 2m 30s\tremaining: 2m 6s\n", "543:\tlearn: 0.1699041\ttotal: 2m 30s\tremaining: 2m 6s\n", "544:\tlearn: 0.1699038\ttotal: 2m 31s\tremaining: 2m 6s\n", "545:\tlearn: 0.1699036\ttotal: 2m 31s\tremaining: 2m 5s\n", "546:\tlearn: 0.1699033\ttotal: 2m 31s\tremaining: 2m 5s\n", "547:\tlearn: 0.1699030\ttotal: 2m 31s\tremaining: 2m 5s\n", "548:\tlearn: 0.1699026\ttotal: 2m 32s\tremaining: 2m 4s\n", "549:\tlearn: 0.1699024\ttotal: 2m 32s\tremaining: 2m 4s\n", "550:\tlearn: 0.1699022\ttotal: 2m 32s\tremaining: 2m 4s\n", "551:\tlearn: 0.1699020\ttotal: 2m 32s\tremaining: 2m 4s\n", "552:\tlearn: 0.1699018\ttotal: 2m 33s\tremaining: 2m 3s\n", "553:\tlearn: 0.1699015\ttotal: 2m 33s\tremaining: 2m 3s\n", "554:\tlearn: 0.1699013\ttotal: 2m 33s\tremaining: 2m 3s\n", "555:\tlearn: 0.1699011\ttotal: 2m 33s\tremaining: 2m 2s\n", "556:\tlearn: 0.1699008\ttotal: 2m 34s\tremaining: 2m 2s\n", "557:\tlearn: 0.1699006\ttotal: 2m 34s\tremaining: 2m 2s\n", "558:\tlearn: 0.1699003\ttotal: 2m 34s\tremaining: 2m 2s\n", "559:\tlearn: 0.1699001\ttotal: 2m 34s\tremaining: 2m 1s\n", "560:\tlearn: 0.1698998\ttotal: 2m 35s\tremaining: 2m 1s\n", "561:\tlearn: 0.1698996\ttotal: 2m 35s\tremaining: 2m 1s\n", "562:\tlearn: 0.1698994\ttotal: 2m 35s\tremaining: 2m\n", "563:\tlearn: 0.1698992\ttotal: 2m 36s\tremaining: 2m\n", "564:\tlearn: 0.1698989\ttotal: 2m 36s\tremaining: 2m\n", "565:\tlearn: 0.1698987\ttotal: 2m 36s\tremaining: 2m\n", "566:\tlearn: 0.1698984\ttotal: 2m 36s\tremaining: 1m 59s\n", "567:\tlearn: 0.1698982\ttotal: 2m 37s\tremaining: 1m 59s\n", "568:\tlearn: 0.1698980\ttotal: 2m 37s\tremaining: 1m 59s\n", "569:\tlearn: 0.1698977\ttotal: 2m 37s\tremaining: 1m 58s\n", "570:\tlearn: 0.1698974\ttotal: 2m 38s\tremaining: 1m 58s\n", "571:\tlearn: 0.1698972\ttotal: 2m 38s\tremaining: 1m 58s\n", "572:\tlearn: 0.1698970\ttotal: 2m 38s\tremaining: 1m 58s\n", "573:\tlearn: 0.1698969\ttotal: 2m 38s\tremaining: 1m 57s\n", "574:\tlearn: 0.1698967\ttotal: 2m 39s\tremaining: 1m 57s\n", "575:\tlearn: 0.1698965\ttotal: 2m 39s\tremaining: 1m 57s\n", "576:\tlearn: 0.1698962\ttotal: 2m 39s\tremaining: 1m 56s\n", "577:\tlearn: 0.1698960\ttotal: 2m 39s\tremaining: 1m 56s\n", "578:\tlearn: 0.1698959\ttotal: 2m 40s\tremaining: 1m 56s\n", "579:\tlearn: 0.1698957\ttotal: 2m 40s\tremaining: 1m 56s\n", "580:\tlearn: 0.1698955\ttotal: 2m 40s\tremaining: 1m 55s\n", "581:\tlearn: 0.1698953\ttotal: 2m 40s\tremaining: 1m 55s\n", "582:\tlearn: 0.1698950\ttotal: 2m 41s\tremaining: 1m 55s\n", "583:\tlearn: 0.1698948\ttotal: 2m 41s\tremaining: 1m 55s\n", "584:\tlearn: 0.1698946\ttotal: 2m 41s\tremaining: 1m 54s\n", "585:\tlearn: 0.1698944\ttotal: 2m 42s\tremaining: 1m 54s\n", "586:\tlearn: 0.1698942\ttotal: 2m 42s\tremaining: 1m 54s\n", "587:\tlearn: 0.1698941\ttotal: 2m 42s\tremaining: 1m 53s\n", "588:\tlearn: 0.1698940\ttotal: 2m 42s\tremaining: 1m 53s\n", "589:\tlearn: 0.1698938\ttotal: 2m 43s\tremaining: 1m 53s\n", "590:\tlearn: 0.1698936\ttotal: 2m 43s\tremaining: 1m 53s\n", "591:\tlearn: 0.1698934\ttotal: 2m 43s\tremaining: 1m 52s\n", "592:\tlearn: 0.1698933\ttotal: 2m 43s\tremaining: 1m 52s\n", "593:\tlearn: 0.1698931\ttotal: 2m 44s\tremaining: 1m 52s\n", "594:\tlearn: 0.1698930\ttotal: 2m 44s\tremaining: 1m 51s\n", "595:\tlearn: 0.1698928\ttotal: 2m 44s\tremaining: 1m 51s\n", "596:\tlearn: 0.1698926\ttotal: 2m 44s\tremaining: 1m 51s\n", "597:\tlearn: 0.1698924\ttotal: 2m 45s\tremaining: 1m 51s\n", "598:\tlearn: 0.1698923\ttotal: 2m 45s\tremaining: 1m 50s\n", "599:\tlearn: 0.1698920\ttotal: 2m 45s\tremaining: 1m 50s\n", "600:\tlearn: 0.1698919\ttotal: 2m 46s\tremaining: 1m 50s\n", "601:\tlearn: 0.1698917\ttotal: 2m 46s\tremaining: 1m 49s\n", "602:\tlearn: 0.1698915\ttotal: 2m 46s\tremaining: 1m 49s\n", "603:\tlearn: 0.1698914\ttotal: 2m 46s\tremaining: 1m 49s\n", "604:\tlearn: 0.1698912\ttotal: 2m 47s\tremaining: 1m 49s\n", "605:\tlearn: 0.1698911\ttotal: 2m 47s\tremaining: 1m 48s\n", "606:\tlearn: 0.1698910\ttotal: 2m 47s\tremaining: 1m 48s\n", "607:\tlearn: 0.1698908\ttotal: 2m 47s\tremaining: 1m 48s\n", "608:\tlearn: 0.1698907\ttotal: 2m 48s\tremaining: 1m 47s\n", "609:\tlearn: 0.1698905\ttotal: 2m 48s\tremaining: 1m 47s\n", "610:\tlearn: 0.1698903\ttotal: 2m 48s\tremaining: 1m 47s\n", "611:\tlearn: 0.1698902\ttotal: 2m 48s\tremaining: 1m 47s\n", "612:\tlearn: 0.1698901\ttotal: 2m 49s\tremaining: 1m 46s\n", "613:\tlearn: 0.1698899\ttotal: 2m 49s\tremaining: 1m 46s\n", "614:\tlearn: 0.1698897\ttotal: 2m 49s\tremaining: 1m 46s\n", "615:\tlearn: 0.1698895\ttotal: 2m 50s\tremaining: 1m 46s\n", "616:\tlearn: 0.1698893\ttotal: 2m 50s\tremaining: 1m 45s\n", "617:\tlearn: 0.1698893\ttotal: 2m 50s\tremaining: 1m 45s\n", "618:\tlearn: 0.1698891\ttotal: 2m 50s\tremaining: 1m 45s\n", "619:\tlearn: 0.1698890\ttotal: 2m 51s\tremaining: 1m 44s\n", "620:\tlearn: 0.1698888\ttotal: 2m 51s\tremaining: 1m 44s\n", "621:\tlearn: 0.1698886\ttotal: 2m 51s\tremaining: 1m 44s\n", "622:\tlearn: 0.1698884\ttotal: 2m 52s\tremaining: 1m 44s\n", "623:\tlearn: 0.1698883\ttotal: 2m 52s\tremaining: 1m 43s\n", "624:\tlearn: 0.1698881\ttotal: 2m 52s\tremaining: 1m 43s\n", "625:\tlearn: 0.1698880\ttotal: 2m 52s\tremaining: 1m 43s\n", "626:\tlearn: 0.1698879\ttotal: 2m 53s\tremaining: 1m 43s\n", "627:\tlearn: 0.1698878\ttotal: 2m 53s\tremaining: 1m 42s\n", "628:\tlearn: 0.1698876\ttotal: 2m 53s\tremaining: 1m 42s\n", "629:\tlearn: 0.1698875\ttotal: 2m 53s\tremaining: 1m 42s\n", "630:\tlearn: 0.1698874\ttotal: 2m 54s\tremaining: 1m 41s\n", "631:\tlearn: 0.1698873\ttotal: 2m 54s\tremaining: 1m 41s\n", "632:\tlearn: 0.1698871\ttotal: 2m 54s\tremaining: 1m 41s\n", "633:\tlearn: 0.1698869\ttotal: 2m 54s\tremaining: 1m 41s\n", "634:\tlearn: 0.1698868\ttotal: 2m 55s\tremaining: 1m 40s\n", "635:\tlearn: 0.1698867\ttotal: 2m 55s\tremaining: 1m 40s\n", "636:\tlearn: 0.1698865\ttotal: 2m 55s\tremaining: 1m 40s\n", "637:\tlearn: 0.1698864\ttotal: 2m 56s\tremaining: 1m 39s\n", "638:\tlearn: 0.1698862\ttotal: 2m 56s\tremaining: 1m 39s\n", "639:\tlearn: 0.1698861\ttotal: 2m 56s\tremaining: 1m 39s\n", "640:\tlearn: 0.1698860\ttotal: 2m 56s\tremaining: 1m 39s\n", "641:\tlearn: 0.1698858\ttotal: 2m 57s\tremaining: 1m 38s\n", "642:\tlearn: 0.1698857\ttotal: 2m 57s\tremaining: 1m 38s\n", "643:\tlearn: 0.1698855\ttotal: 2m 57s\tremaining: 1m 38s\n", "644:\tlearn: 0.1698854\ttotal: 2m 58s\tremaining: 1m 38s\n", "645:\tlearn: 0.1698853\ttotal: 2m 58s\tremaining: 1m 37s\n", "646:\tlearn: 0.1698852\ttotal: 2m 58s\tremaining: 1m 37s\n", "647:\tlearn: 0.1698851\ttotal: 2m 58s\tremaining: 1m 37s\n", "648:\tlearn: 0.1698850\ttotal: 2m 59s\tremaining: 1m 36s\n", "649:\tlearn: 0.1698849\ttotal: 2m 59s\tremaining: 1m 36s\n", "650:\tlearn: 0.1698848\ttotal: 2m 59s\tremaining: 1m 36s\n", "651:\tlearn: 0.1698847\ttotal: 3m\tremaining: 1m 36s\n", "652:\tlearn: 0.1698846\ttotal: 3m\tremaining: 1m 35s\n", "653:\tlearn: 0.1698845\ttotal: 3m\tremaining: 1m 35s\n", "654:\tlearn: 0.1698845\ttotal: 3m\tremaining: 1m 35s\n", "655:\tlearn: 0.1698844\ttotal: 3m 1s\tremaining: 1m 34s\n", "656:\tlearn: 0.1698843\ttotal: 3m 1s\tremaining: 1m 34s\n", "657:\tlearn: 0.1698842\ttotal: 3m 1s\tremaining: 1m 34s\n", "658:\tlearn: 0.1698841\ttotal: 3m 1s\tremaining: 1m 34s\n", "659:\tlearn: 0.1698840\ttotal: 3m 2s\tremaining: 1m 33s\n", "660:\tlearn: 0.1698838\ttotal: 3m 2s\tremaining: 1m 33s\n", "661:\tlearn: 0.1698837\ttotal: 3m 2s\tremaining: 1m 33s\n", "662:\tlearn: 0.1698837\ttotal: 3m 3s\tremaining: 1m 33s\n", "663:\tlearn: 0.1698835\ttotal: 3m 3s\tremaining: 1m 32s\n", "664:\tlearn: 0.1698835\ttotal: 3m 3s\tremaining: 1m 32s\n", "665:\tlearn: 0.1698833\ttotal: 3m 3s\tremaining: 1m 32s\n", "666:\tlearn: 0.1698832\ttotal: 3m 4s\tremaining: 1m 31s\n", "667:\tlearn: 0.1698831\ttotal: 3m 4s\tremaining: 1m 31s\n", "668:\tlearn: 0.1698830\ttotal: 3m 4s\tremaining: 1m 31s\n", "669:\tlearn: 0.1698829\ttotal: 3m 5s\tremaining: 1m 31s\n", "670:\tlearn: 0.1698828\ttotal: 3m 5s\tremaining: 1m 30s\n", "671:\tlearn: 0.1698827\ttotal: 3m 5s\tremaining: 1m 30s\n", "672:\tlearn: 0.1698826\ttotal: 3m 5s\tremaining: 1m 30s\n", "673:\tlearn: 0.1698825\ttotal: 3m 6s\tremaining: 1m 30s\n", "674:\tlearn: 0.1698824\ttotal: 3m 6s\tremaining: 1m 29s\n", "675:\tlearn: 0.1698822\ttotal: 3m 6s\tremaining: 1m 29s\n", "676:\tlearn: 0.1698822\ttotal: 3m 6s\tremaining: 1m 29s\n", "677:\tlearn: 0.1698821\ttotal: 3m 7s\tremaining: 1m 28s\n", "678:\tlearn: 0.1698820\ttotal: 3m 7s\tremaining: 1m 28s\n", "679:\tlearn: 0.1698819\ttotal: 3m 7s\tremaining: 1m 28s\n", "680:\tlearn: 0.1698818\ttotal: 3m 8s\tremaining: 1m 28s\n", "681:\tlearn: 0.1698817\ttotal: 3m 8s\tremaining: 1m 27s\n", "682:\tlearn: 0.1698817\ttotal: 3m 8s\tremaining: 1m 27s\n", "683:\tlearn: 0.1698816\ttotal: 3m 8s\tremaining: 1m 27s\n", "684:\tlearn: 0.1698815\ttotal: 3m 9s\tremaining: 1m 27s\n", "685:\tlearn: 0.1698814\ttotal: 3m 9s\tremaining: 1m 26s\n", "686:\tlearn: 0.1698813\ttotal: 3m 9s\tremaining: 1m 26s\n", "687:\tlearn: 0.1698813\ttotal: 3m 10s\tremaining: 1m 26s\n", "688:\tlearn: 0.1698812\ttotal: 3m 10s\tremaining: 1m 25s\n", "689:\tlearn: 0.1698811\ttotal: 3m 10s\tremaining: 1m 25s\n", "690:\tlearn: 0.1698810\ttotal: 3m 10s\tremaining: 1m 25s\n", "691:\tlearn: 0.1698810\ttotal: 3m 11s\tremaining: 1m 25s\n", "692:\tlearn: 0.1698808\ttotal: 3m 11s\tremaining: 1m 24s\n", "693:\tlearn: 0.1698808\ttotal: 3m 11s\tremaining: 1m 24s\n", "694:\tlearn: 0.1698807\ttotal: 3m 12s\tremaining: 1m 24s\n", "695:\tlearn: 0.1698806\ttotal: 3m 12s\tremaining: 1m 24s\n", "696:\tlearn: 0.1698805\ttotal: 3m 12s\tremaining: 1m 23s\n", "697:\tlearn: 0.1698805\ttotal: 3m 12s\tremaining: 1m 23s\n", "698:\tlearn: 0.1698804\ttotal: 3m 13s\tremaining: 1m 23s\n", "699:\tlearn: 0.1698803\ttotal: 3m 13s\tremaining: 1m 22s\n", "700:\tlearn: 0.1698802\ttotal: 3m 13s\tremaining: 1m 22s\n", "701:\tlearn: 0.1698802\ttotal: 3m 14s\tremaining: 1m 22s\n", "702:\tlearn: 0.1698801\ttotal: 3m 14s\tremaining: 1m 22s\n", "703:\tlearn: 0.1698800\ttotal: 3m 14s\tremaining: 1m 21s\n", "704:\tlearn: 0.1698799\ttotal: 3m 14s\tremaining: 1m 21s\n", "705:\tlearn: 0.1698799\ttotal: 3m 15s\tremaining: 1m 21s\n", "706:\tlearn: 0.1698798\ttotal: 3m 15s\tremaining: 1m 20s\n", "707:\tlearn: 0.1698797\ttotal: 3m 15s\tremaining: 1m 20s\n", "708:\tlearn: 0.1698796\ttotal: 3m 16s\tremaining: 1m 20s\n", "709:\tlearn: 0.1698795\ttotal: 3m 16s\tremaining: 1m 20s\n", "710:\tlearn: 0.1698794\ttotal: 3m 16s\tremaining: 1m 19s\n", "711:\tlearn: 0.1698793\ttotal: 3m 16s\tremaining: 1m 19s\n", "712:\tlearn: 0.1698793\ttotal: 3m 17s\tremaining: 1m 19s\n", "713:\tlearn: 0.1698792\ttotal: 3m 17s\tremaining: 1m 19s\n", "714:\tlearn: 0.1698791\ttotal: 3m 17s\tremaining: 1m 18s\n", "715:\tlearn: 0.1698790\ttotal: 3m 18s\tremaining: 1m 18s\n", "716:\tlearn: 0.1698790\ttotal: 3m 18s\tremaining: 1m 18s\n", "717:\tlearn: 0.1698789\ttotal: 3m 18s\tremaining: 1m 18s\n", "718:\tlearn: 0.1698789\ttotal: 3m 18s\tremaining: 1m 17s\n", "719:\tlearn: 0.1698788\ttotal: 3m 19s\tremaining: 1m 17s\n", "720:\tlearn: 0.1698787\ttotal: 3m 19s\tremaining: 1m 17s\n", "721:\tlearn: 0.1698787\ttotal: 3m 19s\tremaining: 1m 16s\n", "722:\tlearn: 0.1698786\ttotal: 3m 19s\tremaining: 1m 16s\n", "723:\tlearn: 0.1698785\ttotal: 3m 20s\tremaining: 1m 16s\n", "724:\tlearn: 0.1698784\ttotal: 3m 20s\tremaining: 1m 16s\n", "725:\tlearn: 0.1698784\ttotal: 3m 20s\tremaining: 1m 15s\n", "726:\tlearn: 0.1698783\ttotal: 3m 21s\tremaining: 1m 15s\n", "727:\tlearn: 0.1698782\ttotal: 3m 21s\tremaining: 1m 15s\n", "728:\tlearn: 0.1698782\ttotal: 3m 21s\tremaining: 1m 14s\n", "729:\tlearn: 0.1698781\ttotal: 3m 22s\tremaining: 1m 14s\n", "730:\tlearn: 0.1698781\ttotal: 3m 22s\tremaining: 1m 14s\n", "731:\tlearn: 0.1698780\ttotal: 3m 22s\tremaining: 1m 14s\n", "732:\tlearn: 0.1698780\ttotal: 3m 22s\tremaining: 1m 13s\n", "733:\tlearn: 0.1698779\ttotal: 3m 23s\tremaining: 1m 13s\n", "734:\tlearn: 0.1698779\ttotal: 3m 23s\tremaining: 1m 13s\n", "735:\tlearn: 0.1698778\ttotal: 3m 23s\tremaining: 1m 13s\n", "736:\tlearn: 0.1698778\ttotal: 3m 23s\tremaining: 1m 12s\n", "737:\tlearn: 0.1698777\ttotal: 3m 24s\tremaining: 1m 12s\n", "738:\tlearn: 0.1698777\ttotal: 3m 24s\tremaining: 1m 12s\n", "739:\tlearn: 0.1698776\ttotal: 3m 24s\tremaining: 1m 11s\n", "740:\tlearn: 0.1698776\ttotal: 3m 24s\tremaining: 1m 11s\n", "741:\tlearn: 0.1698775\ttotal: 3m 25s\tremaining: 1m 11s\n", "742:\tlearn: 0.1698774\ttotal: 3m 25s\tremaining: 1m 11s\n", "743:\tlearn: 0.1698774\ttotal: 3m 25s\tremaining: 1m 10s\n", "744:\tlearn: 0.1698773\ttotal: 3m 26s\tremaining: 1m 10s\n", "745:\tlearn: 0.1698772\ttotal: 3m 26s\tremaining: 1m 10s\n", "746:\tlearn: 0.1698772\ttotal: 3m 26s\tremaining: 1m 9s\n", "747:\tlearn: 0.1698771\ttotal: 3m 26s\tremaining: 1m 9s\n", "748:\tlearn: 0.1698770\ttotal: 3m 27s\tremaining: 1m 9s\n", "749:\tlearn: 0.1698770\ttotal: 3m 27s\tremaining: 1m 9s\n", "750:\tlearn: 0.1698770\ttotal: 3m 27s\tremaining: 1m 8s\n", "751:\tlearn: 0.1698769\ttotal: 3m 27s\tremaining: 1m 8s\n", "752:\tlearn: 0.1698769\ttotal: 3m 28s\tremaining: 1m 8s\n", "753:\tlearn: 0.1698768\ttotal: 3m 28s\tremaining: 1m 7s\n", "754:\tlearn: 0.1698768\ttotal: 3m 28s\tremaining: 1m 7s\n", "755:\tlearn: 0.1698768\ttotal: 3m 28s\tremaining: 1m 7s\n", "756:\tlearn: 0.1698767\ttotal: 3m 29s\tremaining: 1m 7s\n", "757:\tlearn: 0.1698767\ttotal: 3m 29s\tremaining: 1m 6s\n", "758:\tlearn: 0.1698766\ttotal: 3m 29s\tremaining: 1m 6s\n", "759:\tlearn: 0.1698766\ttotal: 3m 30s\tremaining: 1m 6s\n", "760:\tlearn: 0.1698765\ttotal: 3m 30s\tremaining: 1m 6s\n", "761:\tlearn: 0.1698765\ttotal: 3m 30s\tremaining: 1m 5s\n", "762:\tlearn: 0.1698764\ttotal: 3m 30s\tremaining: 1m 5s\n", "763:\tlearn: 0.1698764\ttotal: 3m 31s\tremaining: 1m 5s\n", "764:\tlearn: 0.1698764\ttotal: 3m 31s\tremaining: 1m 4s\n", "765:\tlearn: 0.1698763\ttotal: 3m 31s\tremaining: 1m 4s\n", "766:\tlearn: 0.1698763\ttotal: 3m 31s\tremaining: 1m 4s\n", "767:\tlearn: 0.1698762\ttotal: 3m 32s\tremaining: 1m 4s\n", "768:\tlearn: 0.1698762\ttotal: 3m 32s\tremaining: 1m 3s\n", "769:\tlearn: 0.1698761\ttotal: 3m 32s\tremaining: 1m 3s\n", "770:\tlearn: 0.1698761\ttotal: 3m 33s\tremaining: 1m 3s\n", "771:\tlearn: 0.1698761\ttotal: 3m 33s\tremaining: 1m 2s\n", "772:\tlearn: 0.1698760\ttotal: 3m 33s\tremaining: 1m 2s\n", "773:\tlearn: 0.1698760\ttotal: 3m 33s\tremaining: 1m 2s\n", "774:\tlearn: 0.1698759\ttotal: 3m 33s\tremaining: 1m 2s\n", "775:\tlearn: 0.1698759\ttotal: 3m 34s\tremaining: 1m 1s\n", "776:\tlearn: 0.1698758\ttotal: 3m 34s\tremaining: 1m 1s\n", "777:\tlearn: 0.1698758\ttotal: 3m 34s\tremaining: 1m 1s\n", "778:\tlearn: 0.1698757\ttotal: 3m 35s\tremaining: 1m 1s\n", "779:\tlearn: 0.1698757\ttotal: 3m 35s\tremaining: 1m\n", "780:\tlearn: 0.1698757\ttotal: 3m 35s\tremaining: 1m\n", "781:\tlearn: 0.1698756\ttotal: 3m 35s\tremaining: 1m\n", "782:\tlearn: 0.1698756\ttotal: 3m 36s\tremaining: 59.9s\n", "783:\tlearn: 0.1698756\ttotal: 3m 36s\tremaining: 59.6s\n", "784:\tlearn: 0.1698755\ttotal: 3m 36s\tremaining: 59.3s\n", "785:\tlearn: 0.1698755\ttotal: 3m 36s\tremaining: 59.1s\n", "786:\tlearn: 0.1698755\ttotal: 3m 37s\tremaining: 58.8s\n", "787:\tlearn: 0.1698754\ttotal: 3m 37s\tremaining: 58.5s\n", "788:\tlearn: 0.1698754\ttotal: 3m 37s\tremaining: 58.2s\n", "789:\tlearn: 0.1698754\ttotal: 3m 37s\tremaining: 57.9s\n", "790:\tlearn: 0.1698753\ttotal: 3m 38s\tremaining: 57.7s\n", "791:\tlearn: 0.1698753\ttotal: 3m 38s\tremaining: 57.4s\n", "792:\tlearn: 0.1698753\ttotal: 3m 38s\tremaining: 57.1s\n", "793:\tlearn: 0.1698752\ttotal: 3m 39s\tremaining: 56.9s\n", "794:\tlearn: 0.1698752\ttotal: 3m 39s\tremaining: 56.6s\n", "795:\tlearn: 0.1698751\ttotal: 3m 39s\tremaining: 56.3s\n", "796:\tlearn: 0.1698751\ttotal: 3m 39s\tremaining: 56s\n", "797:\tlearn: 0.1698751\ttotal: 3m 40s\tremaining: 55.7s\n", "798:\tlearn: 0.1698750\ttotal: 3m 40s\tremaining: 55.5s\n", "799:\tlearn: 0.1698750\ttotal: 3m 40s\tremaining: 55.2s\n", "800:\tlearn: 0.1698750\ttotal: 3m 41s\tremaining: 54.9s\n", "801:\tlearn: 0.1698749\ttotal: 3m 41s\tremaining: 54.6s\n", "802:\tlearn: 0.1698749\ttotal: 3m 41s\tremaining: 54.3s\n", "803:\tlearn: 0.1698749\ttotal: 3m 41s\tremaining: 54.1s\n", "804:\tlearn: 0.1698748\ttotal: 3m 42s\tremaining: 53.8s\n", "805:\tlearn: 0.1698748\ttotal: 3m 42s\tremaining: 53.5s\n", "806:\tlearn: 0.1698748\ttotal: 3m 42s\tremaining: 53.2s\n", "807:\tlearn: 0.1698748\ttotal: 3m 42s\tremaining: 53s\n", "808:\tlearn: 0.1698747\ttotal: 3m 43s\tremaining: 52.7s\n", "809:\tlearn: 0.1698747\ttotal: 3m 43s\tremaining: 52.4s\n", "810:\tlearn: 0.1698747\ttotal: 3m 43s\tremaining: 52.1s\n", "811:\tlearn: 0.1698746\ttotal: 3m 43s\tremaining: 51.9s\n", "812:\tlearn: 0.1698746\ttotal: 3m 44s\tremaining: 51.6s\n", "813:\tlearn: 0.1698746\ttotal: 3m 44s\tremaining: 51.3s\n", "814:\tlearn: 0.1698745\ttotal: 3m 44s\tremaining: 51s\n", "815:\tlearn: 0.1698745\ttotal: 3m 45s\tremaining: 50.8s\n", "816:\tlearn: 0.1698745\ttotal: 3m 45s\tremaining: 50.5s\n", "817:\tlearn: 0.1698744\ttotal: 3m 45s\tremaining: 50.2s\n", "818:\tlearn: 0.1698744\ttotal: 3m 45s\tremaining: 49.9s\n", "819:\tlearn: 0.1698744\ttotal: 3m 46s\tremaining: 49.7s\n", "820:\tlearn: 0.1698743\ttotal: 3m 46s\tremaining: 49.4s\n", "821:\tlearn: 0.1698743\ttotal: 3m 46s\tremaining: 49.1s\n", "822:\tlearn: 0.1698743\ttotal: 3m 47s\tremaining: 48.9s\n", "823:\tlearn: 0.1698742\ttotal: 3m 47s\tremaining: 48.6s\n", "824:\tlearn: 0.1698742\ttotal: 3m 47s\tremaining: 48.3s\n", "825:\tlearn: 0.1698742\ttotal: 3m 48s\tremaining: 48s\n", "826:\tlearn: 0.1698741\ttotal: 3m 48s\tremaining: 47.8s\n", "827:\tlearn: 0.1698741\ttotal: 3m 48s\tremaining: 47.5s\n", "828:\tlearn: 0.1698741\ttotal: 3m 48s\tremaining: 47.2s\n", "829:\tlearn: 0.1698740\ttotal: 3m 49s\tremaining: 46.9s\n", "830:\tlearn: 0.1698740\ttotal: 3m 49s\tremaining: 46.6s\n", "831:\tlearn: 0.1698740\ttotal: 3m 49s\tremaining: 46.4s\n", "832:\tlearn: 0.1698739\ttotal: 3m 49s\tremaining: 46.1s\n", "833:\tlearn: 0.1698739\ttotal: 3m 50s\tremaining: 45.8s\n", "834:\tlearn: 0.1698739\ttotal: 3m 50s\tremaining: 45.5s\n", "835:\tlearn: 0.1698739\ttotal: 3m 50s\tremaining: 45.3s\n", "836:\tlearn: 0.1698738\ttotal: 3m 50s\tremaining: 45s\n", "837:\tlearn: 0.1698738\ttotal: 3m 51s\tremaining: 44.7s\n", "838:\tlearn: 0.1698738\ttotal: 3m 51s\tremaining: 44.4s\n", "839:\tlearn: 0.1698737\ttotal: 3m 51s\tremaining: 44.1s\n", "840:\tlearn: 0.1698737\ttotal: 3m 52s\tremaining: 43.9s\n", "841:\tlearn: 0.1698737\ttotal: 3m 52s\tremaining: 43.6s\n", "842:\tlearn: 0.1698737\ttotal: 3m 52s\tremaining: 43.3s\n", "843:\tlearn: 0.1698736\ttotal: 3m 52s\tremaining: 43s\n", "844:\tlearn: 0.1698736\ttotal: 3m 53s\tremaining: 42.8s\n", "845:\tlearn: 0.1698736\ttotal: 3m 53s\tremaining: 42.5s\n", "846:\tlearn: 0.1698736\ttotal: 3m 53s\tremaining: 42.2s\n", "847:\tlearn: 0.1698735\ttotal: 3m 54s\tremaining: 42s\n", "848:\tlearn: 0.1698735\ttotal: 3m 54s\tremaining: 41.7s\n", "849:\tlearn: 0.1698735\ttotal: 3m 54s\tremaining: 41.4s\n", "850:\tlearn: 0.1698735\ttotal: 3m 54s\tremaining: 41.1s\n", "851:\tlearn: 0.1698735\ttotal: 3m 55s\tremaining: 40.8s\n", "852:\tlearn: 0.1698734\ttotal: 3m 55s\tremaining: 40.6s\n", "853:\tlearn: 0.1698734\ttotal: 3m 55s\tremaining: 40.3s\n", "854:\tlearn: 0.1698734\ttotal: 3m 56s\tremaining: 40s\n", "855:\tlearn: 0.1698734\ttotal: 3m 56s\tremaining: 39.8s\n", "856:\tlearn: 0.1698733\ttotal: 3m 56s\tremaining: 39.5s\n", "857:\tlearn: 0.1698733\ttotal: 3m 56s\tremaining: 39.2s\n", "858:\tlearn: 0.1698733\ttotal: 3m 57s\tremaining: 38.9s\n", "859:\tlearn: 0.1698732\ttotal: 3m 57s\tremaining: 38.7s\n", "860:\tlearn: 0.1698732\ttotal: 3m 57s\tremaining: 38.4s\n", "861:\tlearn: 0.1698732\ttotal: 3m 58s\tremaining: 38.1s\n", "862:\tlearn: 0.1698732\ttotal: 3m 58s\tremaining: 37.8s\n", "863:\tlearn: 0.1698732\ttotal: 3m 58s\tremaining: 37.5s\n", "864:\tlearn: 0.1698731\ttotal: 3m 58s\tremaining: 37.3s\n", "865:\tlearn: 0.1698731\ttotal: 3m 59s\tremaining: 37s\n", "866:\tlearn: 0.1698731\ttotal: 3m 59s\tremaining: 36.7s\n", "867:\tlearn: 0.1698731\ttotal: 3m 59s\tremaining: 36.4s\n", "868:\tlearn: 0.1698731\ttotal: 3m 59s\tremaining: 36.2s\n", "869:\tlearn: 0.1698730\ttotal: 4m\tremaining: 35.9s\n", "870:\tlearn: 0.1698730\ttotal: 4m\tremaining: 35.6s\n", "871:\tlearn: 0.1698730\ttotal: 4m\tremaining: 35.3s\n", "872:\tlearn: 0.1698730\ttotal: 4m 1s\tremaining: 35.1s\n", "873:\tlearn: 0.1698729\ttotal: 4m 1s\tremaining: 34.8s\n", "874:\tlearn: 0.1698729\ttotal: 4m 1s\tremaining: 34.5s\n", "875:\tlearn: 0.1698729\ttotal: 4m 1s\tremaining: 34.2s\n", "876:\tlearn: 0.1698729\ttotal: 4m 2s\tremaining: 34s\n", "877:\tlearn: 0.1698729\ttotal: 4m 2s\tremaining: 33.7s\n", "878:\tlearn: 0.1698729\ttotal: 4m 2s\tremaining: 33.4s\n", "879:\tlearn: 0.1698729\ttotal: 4m 3s\tremaining: 33.1s\n", "880:\tlearn: 0.1698728\ttotal: 4m 3s\tremaining: 32.9s\n", "881:\tlearn: 0.1698728\ttotal: 4m 3s\tremaining: 32.6s\n", "882:\tlearn: 0.1698728\ttotal: 4m 3s\tremaining: 32.3s\n", "883:\tlearn: 0.1698728\ttotal: 4m 4s\tremaining: 32s\n", "884:\tlearn: 0.1698728\ttotal: 4m 4s\tremaining: 31.7s\n", "885:\tlearn: 0.1698728\ttotal: 4m 4s\tremaining: 31.5s\n", "886:\tlearn: 0.1698727\ttotal: 4m 4s\tremaining: 31.2s\n", "887:\tlearn: 0.1698727\ttotal: 4m 5s\tremaining: 30.9s\n", "888:\tlearn: 0.1698727\ttotal: 4m 5s\tremaining: 30.6s\n", "889:\tlearn: 0.1698727\ttotal: 4m 5s\tremaining: 30.4s\n", "890:\tlearn: 0.1698727\ttotal: 4m 6s\tremaining: 30.1s\n", "891:\tlearn: 0.1698726\ttotal: 4m 6s\tremaining: 29.8s\n", "892:\tlearn: 0.1698726\ttotal: 4m 6s\tremaining: 29.5s\n", "893:\tlearn: 0.1698726\ttotal: 4m 6s\tremaining: 29.3s\n", "894:\tlearn: 0.1698726\ttotal: 4m 7s\tremaining: 29s\n", "895:\tlearn: 0.1698726\ttotal: 4m 7s\tremaining: 28.7s\n", "896:\tlearn: 0.1698726\ttotal: 4m 7s\tremaining: 28.4s\n", "897:\tlearn: 0.1698726\ttotal: 4m 7s\tremaining: 28.2s\n", "898:\tlearn: 0.1698725\ttotal: 4m 8s\tremaining: 27.9s\n", "899:\tlearn: 0.1698725\ttotal: 4m 8s\tremaining: 27.6s\n", "900:\tlearn: 0.1698725\ttotal: 4m 8s\tremaining: 27.3s\n", "901:\tlearn: 0.1698725\ttotal: 4m 8s\tremaining: 27s\n", "902:\tlearn: 0.1698725\ttotal: 4m 9s\tremaining: 26.8s\n", "903:\tlearn: 0.1698725\ttotal: 4m 9s\tremaining: 26.5s\n", "904:\tlearn: 0.1698724\ttotal: 4m 9s\tremaining: 26.2s\n", "905:\tlearn: 0.1698724\ttotal: 4m 9s\tremaining: 25.9s\n", "906:\tlearn: 0.1698724\ttotal: 4m 10s\tremaining: 25.7s\n", "907:\tlearn: 0.1698724\ttotal: 4m 10s\tremaining: 25.4s\n", "908:\tlearn: 0.1698724\ttotal: 4m 10s\tremaining: 25.1s\n", "909:\tlearn: 0.1698724\ttotal: 4m 11s\tremaining: 24.8s\n", "910:\tlearn: 0.1698723\ttotal: 4m 11s\tremaining: 24.6s\n", "911:\tlearn: 0.1698723\ttotal: 4m 11s\tremaining: 24.3s\n", "912:\tlearn: 0.1698723\ttotal: 4m 11s\tremaining: 24s\n", "913:\tlearn: 0.1698723\ttotal: 4m 12s\tremaining: 23.7s\n", "914:\tlearn: 0.1698723\ttotal: 4m 12s\tremaining: 23.5s\n", "915:\tlearn: 0.1698723\ttotal: 4m 12s\tremaining: 23.2s\n", "916:\tlearn: 0.1698723\ttotal: 4m 13s\tremaining: 22.9s\n", "917:\tlearn: 0.1698723\ttotal: 4m 13s\tremaining: 22.6s\n", "918:\tlearn: 0.1698722\ttotal: 4m 13s\tremaining: 22.3s\n", "919:\tlearn: 0.1698722\ttotal: 4m 13s\tremaining: 22.1s\n", "920:\tlearn: 0.1698722\ttotal: 4m 14s\tremaining: 21.8s\n", "921:\tlearn: 0.1698722\ttotal: 4m 14s\tremaining: 21.5s\n", "922:\tlearn: 0.1698722\ttotal: 4m 14s\tremaining: 21.2s\n", "923:\tlearn: 0.1698722\ttotal: 4m 14s\tremaining: 21s\n", "924:\tlearn: 0.1698722\ttotal: 4m 15s\tremaining: 20.7s\n", "925:\tlearn: 0.1698722\ttotal: 4m 15s\tremaining: 20.4s\n", "926:\tlearn: 0.1698721\ttotal: 4m 15s\tremaining: 20.1s\n", "927:\tlearn: 0.1698721\ttotal: 4m 15s\tremaining: 19.9s\n", "928:\tlearn: 0.1698721\ttotal: 4m 16s\tremaining: 19.6s\n", "929:\tlearn: 0.1698721\ttotal: 4m 16s\tremaining: 19.3s\n", "930:\tlearn: 0.1698721\ttotal: 4m 16s\tremaining: 19s\n", "931:\tlearn: 0.1698721\ttotal: 4m 17s\tremaining: 18.8s\n", "932:\tlearn: 0.1698721\ttotal: 4m 17s\tremaining: 18.5s\n", "933:\tlearn: 0.1698721\ttotal: 4m 17s\tremaining: 18.2s\n", "934:\tlearn: 0.1698721\ttotal: 4m 17s\tremaining: 17.9s\n", "935:\tlearn: 0.1698720\ttotal: 4m 18s\tremaining: 17.6s\n", "936:\tlearn: 0.1698720\ttotal: 4m 18s\tremaining: 17.4s\n", "937:\tlearn: 0.1698720\ttotal: 4m 18s\tremaining: 17.1s\n", "938:\tlearn: 0.1698720\ttotal: 4m 18s\tremaining: 16.8s\n", "939:\tlearn: 0.1698720\ttotal: 4m 19s\tremaining: 16.5s\n", "940:\tlearn: 0.1698720\ttotal: 4m 19s\tremaining: 16.3s\n", "941:\tlearn: 0.1698720\ttotal: 4m 19s\tremaining: 16s\n", "942:\tlearn: 0.1698719\ttotal: 4m 20s\tremaining: 15.7s\n", "943:\tlearn: 0.1698719\ttotal: 4m 20s\tremaining: 15.4s\n", "944:\tlearn: 0.1698719\ttotal: 4m 20s\tremaining: 15.2s\n", "945:\tlearn: 0.1698719\ttotal: 4m 20s\tremaining: 14.9s\n", "946:\tlearn: 0.1698719\ttotal: 4m 21s\tremaining: 14.6s\n", "947:\tlearn: 0.1698719\ttotal: 4m 21s\tremaining: 14.3s\n", "948:\tlearn: 0.1698719\ttotal: 4m 21s\tremaining: 14.1s\n", "949:\tlearn: 0.1698719\ttotal: 4m 21s\tremaining: 13.8s\n", "950:\tlearn: 0.1698719\ttotal: 4m 22s\tremaining: 13.5s\n", "951:\tlearn: 0.1698719\ttotal: 4m 22s\tremaining: 13.2s\n", "952:\tlearn: 0.1698718\ttotal: 4m 22s\tremaining: 13s\n", "953:\tlearn: 0.1698718\ttotal: 4m 22s\tremaining: 12.7s\n", "954:\tlearn: 0.1698718\ttotal: 4m 23s\tremaining: 12.4s\n", "955:\tlearn: 0.1698718\ttotal: 4m 23s\tremaining: 12.1s\n", "956:\tlearn: 0.1698718\ttotal: 4m 23s\tremaining: 11.9s\n", "957:\tlearn: 0.1698718\ttotal: 4m 24s\tremaining: 11.6s\n", "958:\tlearn: 0.1698718\ttotal: 4m 24s\tremaining: 11.3s\n", "959:\tlearn: 0.1698718\ttotal: 4m 24s\tremaining: 11s\n", "960:\tlearn: 0.1698718\ttotal: 4m 24s\tremaining: 10.7s\n", "961:\tlearn: 0.1698718\ttotal: 4m 25s\tremaining: 10.5s\n", "962:\tlearn: 0.1698718\ttotal: 4m 25s\tremaining: 10.2s\n", "963:\tlearn: 0.1698717\ttotal: 4m 25s\tremaining: 9.92s\n", "964:\tlearn: 0.1698717\ttotal: 4m 25s\tremaining: 9.64s\n", "965:\tlearn: 0.1698717\ttotal: 4m 26s\tremaining: 9.37s\n", "966:\tlearn: 0.1698717\ttotal: 4m 26s\tremaining: 9.09s\n", "967:\tlearn: 0.1698717\ttotal: 4m 26s\tremaining: 8.82s\n", "968:\tlearn: 0.1698717\ttotal: 4m 27s\tremaining: 8.54s\n", "969:\tlearn: 0.1698717\ttotal: 4m 27s\tremaining: 8.27s\n", "970:\tlearn: 0.1698717\ttotal: 4m 27s\tremaining: 7.99s\n", "971:\tlearn: 0.1698717\ttotal: 4m 27s\tremaining: 7.72s\n", "972:\tlearn: 0.1698716\ttotal: 4m 28s\tremaining: 7.45s\n", "973:\tlearn: 0.1698716\ttotal: 4m 28s\tremaining: 7.17s\n", "974:\tlearn: 0.1698716\ttotal: 4m 28s\tremaining: 6.89s\n", "975:\tlearn: 0.1698716\ttotal: 4m 29s\tremaining: 6.62s\n", "976:\tlearn: 0.1698716\ttotal: 4m 29s\tremaining: 6.34s\n", "977:\tlearn: 0.1698716\ttotal: 4m 29s\tremaining: 6.07s\n", "978:\tlearn: 0.1698716\ttotal: 4m 30s\tremaining: 5.79s\n", "979:\tlearn: 0.1698716\ttotal: 4m 30s\tremaining: 5.52s\n", "980:\tlearn: 0.1698716\ttotal: 4m 30s\tremaining: 5.24s\n", "981:\tlearn: 0.1698716\ttotal: 4m 30s\tremaining: 4.96s\n", "982:\tlearn: 0.1698715\ttotal: 4m 31s\tremaining: 4.69s\n", "983:\tlearn: 0.1698715\ttotal: 4m 31s\tremaining: 4.41s\n", "984:\tlearn: 0.1698715\ttotal: 4m 31s\tremaining: 4.14s\n", "985:\tlearn: 0.1698715\ttotal: 4m 32s\tremaining: 3.86s\n", "986:\tlearn: 0.1698715\ttotal: 4m 32s\tremaining: 3.59s\n", "987:\tlearn: 0.1698715\ttotal: 4m 32s\tremaining: 3.31s\n", "988:\tlearn: 0.1698715\ttotal: 4m 32s\tremaining: 3.03s\n", "989:\tlearn: 0.1698715\ttotal: 4m 33s\tremaining: 2.76s\n", "990:\tlearn: 0.1698715\ttotal: 4m 33s\tremaining: 2.48s\n", "991:\tlearn: 0.1698715\ttotal: 4m 33s\tremaining: 2.21s\n", "992:\tlearn: 0.1698714\ttotal: 4m 33s\tremaining: 1.93s\n", "993:\tlearn: 0.1698714\ttotal: 4m 34s\tremaining: 1.66s\n", "994:\tlearn: 0.1698714\ttotal: 4m 34s\tremaining: 1.38s\n", "995:\tlearn: 0.1698714\ttotal: 4m 34s\tremaining: 1.1s\n", "996:\tlearn: 0.1698714\ttotal: 4m 35s\tremaining: 828ms\n", "997:\tlearn: 0.1698714\ttotal: 4m 35s\tremaining: 552ms\n", "998:\tlearn: 0.1698714\ttotal: 4m 35s\tremaining: 276ms\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "16:16:51 | INFO | Model fitting completed\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "999:\tlearn: 0.1698714\ttotal: 4m 35s\tremaining: 0us\n" ] } ], "source": [ "plib_data = plib.load_plibdata(contexts_ids=[\"HumanCellLine_K562_10xChromium3-scRNA-seq_Replogle22\"])\n", "traindata, _, testdata = plib.split_plibdata_3fold(\n", " plib_data, context_ids=\"HumanCellLine_K562_10xChromium3-scRNA-seq_Replogle22\"\n", ")\n", "model = plib.load_model(\n", " \"Catboost\",\n", " model_args={\n", " \"learning_rate\": 0.75,\n", " \"random_seed\": 11,\n", " \"iterations\": 1000,\n", " \"task_type\": \"CPU\",\n", " },\n", ")\n", "model.fit(traindata)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "We can now evaluate_model results as follows:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "text/plain": [ "0.17545009567806363" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "evaluator.evaluate(model.predict(testdata), testdata)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "Introducing new evaluators is also trivial:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [], "source": [ "@plib.register_evaluator\n", "class CoolEvaluator(plib.PlibEvaluatorMixin):\n", " def evaluate(self, predictions, true_values, context_adata=None) -> float:\n", " return 0.0" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\"CoolEvaluator\" in plib.list_evaluators()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.4" } }, "nbformat": 4, "nbformat_minor": 4 }