diff --git a/model-py/__init__.py b/model-py/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/model-py/model-xgboost.ipynb b/model-py/model-xgboost.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..f9056372d8155779a82212e4f1ee980a88b5ff4e
--- /dev/null
+++ b/model-py/model-xgboost.ipynb
@@ -0,0 +1,1363 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# math and models\n",
+ "import numpy as np\n",
+ "import pandas as pd\n",
+ "import matplotlib as mpl\n",
+ "import matplotlib.pyplot as plt\n",
+ "import xgboost as xgb\n",
+ "import time"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Load dataset\n",
+ "df = pd.read_csv(\"/data/user/mdefende/Projects/ctmodel-ml/data/BigThick_Restricted_cleaned.csv\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array(['Subject', 'Gender', 'Age', 'Hemi', 'Group', 'Ecc', 'Pol',\n",
+ " 'normEcc', 'normPol', 'Sulc0', 'Curv0', 'Curv2', 'Curv5', 'Curv10',\n",
+ " 'PialCurv0', 'PialCurv2', 'PialCurv5', 'PialCurv10', 'Area0',\n",
+ " 'Area2', 'Area5', 'Area10', 'MidArea', 'MidArea2', 'MidArea5',\n",
+ " 'MidArea10', 'PialArea0', 'PialArea2', 'PialArea5', 'PialArea10',\n",
+ " 'LGI0', 'LGI2', 'LGI5', 'LGI10', 'Thick0', 'Thick2', 'Thick5',\n",
+ " 'Thick10'], dtype=object)"
+ ]
+ },
+ "execution_count": 22,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df.columns.values"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Split into test and train dataframes\n",
+ "df_train = df[df.Group == \"Train\"]\n",
+ "df_test = df[df.Group == \"Test\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# df_x are your input features\n",
+ "x_train = pd.concat([df_train[['Age','normEcc','normPol','Sulc0','Curv5','Area5','LGI5','PialCurv5','PialArea5','MidArea5']]])\n",
+ "x_test = pd.concat([df_test[['Age','normEcc','normPol','Sulc0','Curv5','Area5','LGI5','PialCurv5','PialArea5','MidArea5']]])\n",
+ "\n",
+ "# df_y is your output feature (the one you want to predict)\n",
+ "y_train = df_train[['Thick5']]\n",
+ "y_test = df_test[['Thick5']]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Once deleted, variables cannot be recovered. Proceed (y/[n])? y\n"
+ ]
+ }
+ ],
+ "source": [
+ "%reset_selective df"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Testing out Gradient Boost Decision Tree\n",
+ "num_round = 1000\n",
+ "\n",
+ "param = {'tree_method': 'gpu_hist',\n",
+ " 'max_depth': 6,\n",
+ " 'verbosity': 2}\n",
+ "\n",
+ "# Convert input data from numpy to XGBoost format\n",
+ "dtrain = xgb.DMatrix(x_train, y_train)\n",
+ "dtest = xgb.DMatrix(x_test, y_test)\n",
+ "\n",
+ "watchlist = [(dtest,'eval'),(dtrain,'train')]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[0]\teval-rmse:1.01327\ttrain-rmse:1.00714\n",
+ "[1]\teval-rmse:0.745106\ttrain-rmse:0.73975\n",
+ "[2]\teval-rmse:0.566756\ttrain-rmse:0.562508\n",
+ "[3]\teval-rmse:0.453966\ttrain-rmse:0.450665\n",
+ "[4]\teval-rmse:0.382973\ttrain-rmse:0.380653\n",
+ "[5]\teval-rmse:0.340953\ttrain-rmse:0.339498\n",
+ "[6]\teval-rmse:0.316093\ttrain-rmse:0.315466\n",
+ "[7]\teval-rmse:0.301023\ttrain-rmse:0.300895\n",
+ "[8]\teval-rmse:0.292458\ttrain-rmse:0.29264\n",
+ "[9]\teval-rmse:0.286923\ttrain-rmse:0.287395\n",
+ "[10]\teval-rmse:0.284578\ttrain-rmse:0.285057\n",
+ "[11]\teval-rmse:0.282054\ttrain-rmse:0.282767\n",
+ "[12]\teval-rmse:0.279821\ttrain-rmse:0.280509\n",
+ "[13]\teval-rmse:0.278184\ttrain-rmse:0.278962\n",
+ "[14]\teval-rmse:0.277913\ttrain-rmse:0.277876\n",
+ "[15]\teval-rmse:0.276765\ttrain-rmse:0.276749\n",
+ "[16]\teval-rmse:0.275579\ttrain-rmse:0.275568\n",
+ "[17]\teval-rmse:0.274645\ttrain-rmse:0.274511\n",
+ "[18]\teval-rmse:0.274438\ttrain-rmse:0.274138\n",
+ "[19]\teval-rmse:0.274036\ttrain-rmse:0.273642\n",
+ "[20]\teval-rmse:0.273518\ttrain-rmse:0.273103\n",
+ "[21]\teval-rmse:0.273091\ttrain-rmse:0.272517\n",
+ "[22]\teval-rmse:0.272686\ttrain-rmse:0.272103\n",
+ "[23]\teval-rmse:0.272199\ttrain-rmse:0.271542\n",
+ "[24]\teval-rmse:0.272091\ttrain-rmse:0.271325\n",
+ "[25]\teval-rmse:0.272171\ttrain-rmse:0.270806\n",
+ "[26]\teval-rmse:0.271768\ttrain-rmse:0.270352\n",
+ "[27]\teval-rmse:0.271314\ttrain-rmse:0.269829\n",
+ "[28]\teval-rmse:0.270927\ttrain-rmse:0.269342\n",
+ "[29]\teval-rmse:0.270746\ttrain-rmse:0.269053\n",
+ "[30]\teval-rmse:0.270636\ttrain-rmse:0.268897\n",
+ "[31]\teval-rmse:0.270279\ttrain-rmse:0.268535\n",
+ "[32]\teval-rmse:0.27003\ttrain-rmse:0.268239\n",
+ "[33]\teval-rmse:0.269764\ttrain-rmse:0.267914\n",
+ "[34]\teval-rmse:0.26963\ttrain-rmse:0.267729\n",
+ "[35]\teval-rmse:0.269432\ttrain-rmse:0.267456\n",
+ "[36]\teval-rmse:0.269587\ttrain-rmse:0.267231\n",
+ "[37]\teval-rmse:0.269307\ttrain-rmse:0.266969\n",
+ "[38]\teval-rmse:0.269157\ttrain-rmse:0.266773\n",
+ "[39]\teval-rmse:0.2689\ttrain-rmse:0.266464\n",
+ "[40]\teval-rmse:0.268712\ttrain-rmse:0.266282\n",
+ "[41]\teval-rmse:0.268661\ttrain-rmse:0.266154\n",
+ "[42]\teval-rmse:0.268783\ttrain-rmse:0.265886\n",
+ "[43]\teval-rmse:0.268553\ttrain-rmse:0.265607\n",
+ "[44]\teval-rmse:0.268488\ttrain-rmse:0.265515\n",
+ "[45]\teval-rmse:0.268485\ttrain-rmse:0.265449\n",
+ "[46]\teval-rmse:0.268242\ttrain-rmse:0.265134\n",
+ "[47]\teval-rmse:0.268061\ttrain-rmse:0.264944\n",
+ "[48]\teval-rmse:0.267987\ttrain-rmse:0.264821\n",
+ "[49]\teval-rmse:0.26759\ttrain-rmse:0.264413\n",
+ "[50]\teval-rmse:0.267415\ttrain-rmse:0.264147\n",
+ "[51]\teval-rmse:0.267253\ttrain-rmse:0.263958\n",
+ "[52]\teval-rmse:0.267135\ttrain-rmse:0.263818\n",
+ "[53]\teval-rmse:0.26705\ttrain-rmse:0.263639\n",
+ "[54]\teval-rmse:0.266993\ttrain-rmse:0.263553\n",
+ "[55]\teval-rmse:0.266956\ttrain-rmse:0.263446\n",
+ "[56]\teval-rmse:0.266837\ttrain-rmse:0.263299\n",
+ "[57]\teval-rmse:0.266715\ttrain-rmse:0.263159\n",
+ "[58]\teval-rmse:0.266622\ttrain-rmse:0.262985\n",
+ "[59]\teval-rmse:0.266469\ttrain-rmse:0.262816\n",
+ "[60]\teval-rmse:0.266587\ttrain-rmse:0.262655\n",
+ "[61]\teval-rmse:0.266551\ttrain-rmse:0.26254\n",
+ "[62]\teval-rmse:0.266479\ttrain-rmse:0.26246\n",
+ "[63]\teval-rmse:0.266437\ttrain-rmse:0.262376\n",
+ "[64]\teval-rmse:0.266403\ttrain-rmse:0.262323\n",
+ "[65]\teval-rmse:0.266222\ttrain-rmse:0.262082\n",
+ "[66]\teval-rmse:0.266174\ttrain-rmse:0.261965\n",
+ "[67]\teval-rmse:0.266079\ttrain-rmse:0.261788\n",
+ "[68]\teval-rmse:0.266073\ttrain-rmse:0.261744\n",
+ "[69]\teval-rmse:0.266074\ttrain-rmse:0.261608\n",
+ "[70]\teval-rmse:0.265918\ttrain-rmse:0.261398\n",
+ "[71]\teval-rmse:0.26588\ttrain-rmse:0.261347\n",
+ "[72]\teval-rmse:0.2659\ttrain-rmse:0.261271\n",
+ "[73]\teval-rmse:0.265879\ttrain-rmse:0.261193\n",
+ "[74]\teval-rmse:0.265808\ttrain-rmse:0.261041\n",
+ "[75]\teval-rmse:0.265627\ttrain-rmse:0.260811\n",
+ "[76]\teval-rmse:0.265506\ttrain-rmse:0.260666\n",
+ "[77]\teval-rmse:0.26538\ttrain-rmse:0.260485\n",
+ "[78]\teval-rmse:0.265255\ttrain-rmse:0.260347\n",
+ "[79]\teval-rmse:0.265249\ttrain-rmse:0.260316\n",
+ "[80]\teval-rmse:0.265155\ttrain-rmse:0.260167\n",
+ "[81]\teval-rmse:0.265084\ttrain-rmse:0.260063\n",
+ "[82]\teval-rmse:0.264997\ttrain-rmse:0.259939\n",
+ "[83]\teval-rmse:0.264945\ttrain-rmse:0.259878\n",
+ "[84]\teval-rmse:0.264923\ttrain-rmse:0.259832\n",
+ "[85]\teval-rmse:0.264867\ttrain-rmse:0.259744\n",
+ "[86]\teval-rmse:0.264837\ttrain-rmse:0.259707\n",
+ "[87]\teval-rmse:0.264854\ttrain-rmse:0.259636\n",
+ "[88]\teval-rmse:0.264832\ttrain-rmse:0.259591\n",
+ "[89]\teval-rmse:0.26485\ttrain-rmse:0.259418\n",
+ "[90]\teval-rmse:0.264796\ttrain-rmse:0.259335\n",
+ "[91]\teval-rmse:0.264769\ttrain-rmse:0.259261\n",
+ "[92]\teval-rmse:0.264711\ttrain-rmse:0.25917\n",
+ "[93]\teval-rmse:0.264678\ttrain-rmse:0.259107\n",
+ "[94]\teval-rmse:0.264663\ttrain-rmse:0.259057\n",
+ "[95]\teval-rmse:0.264631\ttrain-rmse:0.258972\n",
+ "[96]\teval-rmse:0.264679\ttrain-rmse:0.258925\n",
+ "[97]\teval-rmse:0.264632\ttrain-rmse:0.258849\n",
+ "[98]\teval-rmse:0.264527\ttrain-rmse:0.25869\n",
+ "[99]\teval-rmse:0.264506\ttrain-rmse:0.258647\n",
+ "[100]\teval-rmse:0.264445\ttrain-rmse:0.258515\n",
+ "[101]\teval-rmse:0.264436\ttrain-rmse:0.258467\n",
+ "[102]\teval-rmse:0.264469\ttrain-rmse:0.258397\n",
+ "[103]\teval-rmse:0.26448\ttrain-rmse:0.258365\n",
+ "[104]\teval-rmse:0.264471\ttrain-rmse:0.258252\n",
+ "[105]\teval-rmse:0.264452\ttrain-rmse:0.258198\n",
+ "[106]\teval-rmse:0.264403\ttrain-rmse:0.258104\n",
+ "[107]\teval-rmse:0.264329\ttrain-rmse:0.257998\n",
+ "[108]\teval-rmse:0.264286\ttrain-rmse:0.257957\n",
+ "[109]\teval-rmse:0.264254\ttrain-rmse:0.257897\n",
+ "[110]\teval-rmse:0.264208\ttrain-rmse:0.257805\n",
+ "[111]\teval-rmse:0.264165\ttrain-rmse:0.257709\n",
+ "[112]\teval-rmse:0.264166\ttrain-rmse:0.257644\n",
+ "[113]\teval-rmse:0.264173\ttrain-rmse:0.257584\n",
+ "[114]\teval-rmse:0.264154\ttrain-rmse:0.257531\n",
+ "[115]\teval-rmse:0.264176\ttrain-rmse:0.257467\n",
+ "[116]\teval-rmse:0.264159\ttrain-rmse:0.257434\n",
+ "[117]\teval-rmse:0.264024\ttrain-rmse:0.257241\n",
+ "[118]\teval-rmse:0.263981\ttrain-rmse:0.257164\n",
+ "[119]\teval-rmse:0.263972\ttrain-rmse:0.257081\n",
+ "[120]\teval-rmse:0.263957\ttrain-rmse:0.257042\n",
+ "[121]\teval-rmse:0.263996\ttrain-rmse:0.256965\n",
+ "[122]\teval-rmse:0.263974\ttrain-rmse:0.256893\n",
+ "[123]\teval-rmse:0.263936\ttrain-rmse:0.256846\n",
+ "[124]\teval-rmse:0.263873\ttrain-rmse:0.256701\n",
+ "[125]\teval-rmse:0.263861\ttrain-rmse:0.256602\n",
+ "[126]\teval-rmse:0.263862\ttrain-rmse:0.256548\n",
+ "[127]\teval-rmse:0.263826\ttrain-rmse:0.256416\n",
+ "[128]\teval-rmse:0.263824\ttrain-rmse:0.256353\n",
+ "[129]\teval-rmse:0.263814\ttrain-rmse:0.256322\n",
+ "[130]\teval-rmse:0.263802\ttrain-rmse:0.25628\n",
+ "[131]\teval-rmse:0.263777\ttrain-rmse:0.256224\n",
+ "[132]\teval-rmse:0.263759\ttrain-rmse:0.256177\n",
+ "[133]\teval-rmse:0.263756\ttrain-rmse:0.256156\n",
+ "[134]\teval-rmse:0.263771\ttrain-rmse:0.256108\n",
+ "[135]\teval-rmse:0.263768\ttrain-rmse:0.256067\n",
+ "[136]\teval-rmse:0.263764\ttrain-rmse:0.256046\n",
+ "[137]\teval-rmse:0.263756\ttrain-rmse:0.256026\n",
+ "[138]\teval-rmse:0.26376\ttrain-rmse:0.255986\n",
+ "[139]\teval-rmse:0.263811\ttrain-rmse:0.255929\n",
+ "[140]\teval-rmse:0.263774\ttrain-rmse:0.25587\n",
+ "[141]\teval-rmse:0.263737\ttrain-rmse:0.255776\n",
+ "[142]\teval-rmse:0.263697\ttrain-rmse:0.255695\n",
+ "[143]\teval-rmse:0.263692\ttrain-rmse:0.255662\n",
+ "[144]\teval-rmse:0.263684\ttrain-rmse:0.255609\n",
+ "[145]\teval-rmse:0.263721\ttrain-rmse:0.255537\n",
+ "[146]\teval-rmse:0.263698\ttrain-rmse:0.255446\n",
+ "[147]\teval-rmse:0.263709\ttrain-rmse:0.255351\n",
+ "[148]\teval-rmse:0.263653\ttrain-rmse:0.255262\n",
+ "[149]\teval-rmse:0.263605\ttrain-rmse:0.255184\n",
+ "[150]\teval-rmse:0.263646\ttrain-rmse:0.255145\n",
+ "[151]\teval-rmse:0.263608\ttrain-rmse:0.255094\n",
+ "[152]\teval-rmse:0.263608\ttrain-rmse:0.255061\n",
+ "[153]\teval-rmse:0.26359\ttrain-rmse:0.254976\n",
+ "[154]\teval-rmse:0.263592\ttrain-rmse:0.254905\n",
+ "[155]\teval-rmse:0.263575\ttrain-rmse:0.254872\n",
+ "[156]\teval-rmse:0.263559\ttrain-rmse:0.254831\n",
+ "[157]\teval-rmse:0.263529\ttrain-rmse:0.25476\n",
+ "[158]\teval-rmse:0.263542\ttrain-rmse:0.254708\n",
+ "[159]\teval-rmse:0.263532\ttrain-rmse:0.25467\n",
+ "[160]\teval-rmse:0.263506\ttrain-rmse:0.254616\n",
+ "[161]\teval-rmse:0.2635\ttrain-rmse:0.254557\n",
+ "[162]\teval-rmse:0.263486\ttrain-rmse:0.254532\n",
+ "[163]\teval-rmse:0.263457\ttrain-rmse:0.254486\n",
+ "[164]\teval-rmse:0.263438\ttrain-rmse:0.254423\n",
+ "[165]\teval-rmse:0.263434\ttrain-rmse:0.254395\n",
+ "[166]\teval-rmse:0.263427\ttrain-rmse:0.254374\n",
+ "[167]\teval-rmse:0.263411\ttrain-rmse:0.25433\n",
+ "[168]\teval-rmse:0.263413\ttrain-rmse:0.254287\n",
+ "[169]\teval-rmse:0.263388\ttrain-rmse:0.254228\n",
+ "[170]\teval-rmse:0.263434\ttrain-rmse:0.25418\n",
+ "[171]\teval-rmse:0.263413\ttrain-rmse:0.254147\n",
+ "[172]\teval-rmse:0.263381\ttrain-rmse:0.254102\n",
+ "[173]\teval-rmse:0.263377\ttrain-rmse:0.25403\n",
+ "[174]\teval-rmse:0.263368\ttrain-rmse:0.253999\n",
+ "[175]\teval-rmse:0.263352\ttrain-rmse:0.253909\n",
+ "[176]\teval-rmse:0.263355\ttrain-rmse:0.253876\n",
+ "[177]\teval-rmse:0.263319\ttrain-rmse:0.253781\n",
+ "[178]\teval-rmse:0.263306\ttrain-rmse:0.253739\n",
+ "[179]\teval-rmse:0.263328\ttrain-rmse:0.253712\n",
+ "[180]\teval-rmse:0.263296\ttrain-rmse:0.253651\n",
+ "[181]\teval-rmse:0.263283\ttrain-rmse:0.253591\n",
+ "[182]\teval-rmse:0.263261\ttrain-rmse:0.253559\n",
+ "[183]\teval-rmse:0.263254\ttrain-rmse:0.253544\n",
+ "[184]\teval-rmse:0.263216\ttrain-rmse:0.253474\n",
+ "[185]\teval-rmse:0.263239\ttrain-rmse:0.253425\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[186]\teval-rmse:0.26324\ttrain-rmse:0.253364\n",
+ "[187]\teval-rmse:0.263238\ttrain-rmse:0.253321\n",
+ "[188]\teval-rmse:0.263239\ttrain-rmse:0.253272\n",
+ "[189]\teval-rmse:0.263231\ttrain-rmse:0.253259\n",
+ "[190]\teval-rmse:0.263203\ttrain-rmse:0.253205\n",
+ "[191]\teval-rmse:0.263197\ttrain-rmse:0.253162\n",
+ "[192]\teval-rmse:0.263181\ttrain-rmse:0.253137\n",
+ "[193]\teval-rmse:0.263181\ttrain-rmse:0.253088\n",
+ "[194]\teval-rmse:0.263173\ttrain-rmse:0.253071\n",
+ "[195]\teval-rmse:0.263167\ttrain-rmse:0.253013\n",
+ "[196]\teval-rmse:0.263141\ttrain-rmse:0.252973\n",
+ "[197]\teval-rmse:0.263139\ttrain-rmse:0.252958\n",
+ "[198]\teval-rmse:0.263133\ttrain-rmse:0.252936\n",
+ "[199]\teval-rmse:0.263121\ttrain-rmse:0.252907\n",
+ "[200]\teval-rmse:0.263111\ttrain-rmse:0.252886\n",
+ "[201]\teval-rmse:0.2631\ttrain-rmse:0.25285\n",
+ "[202]\teval-rmse:0.263104\ttrain-rmse:0.2528\n",
+ "[203]\teval-rmse:0.263104\ttrain-rmse:0.252751\n",
+ "[204]\teval-rmse:0.263095\ttrain-rmse:0.25274\n",
+ "[205]\teval-rmse:0.263105\ttrain-rmse:0.252699\n",
+ "[206]\teval-rmse:0.263073\ttrain-rmse:0.25264\n",
+ "[207]\teval-rmse:0.263053\ttrain-rmse:0.252603\n",
+ "[208]\teval-rmse:0.263046\ttrain-rmse:0.252567\n",
+ "[209]\teval-rmse:0.263039\ttrain-rmse:0.252526\n",
+ "[210]\teval-rmse:0.263036\ttrain-rmse:0.252504\n",
+ "[211]\teval-rmse:0.263049\ttrain-rmse:0.25246\n",
+ "[212]\teval-rmse:0.263088\ttrain-rmse:0.252396\n",
+ "[213]\teval-rmse:0.263069\ttrain-rmse:0.252354\n",
+ "[214]\teval-rmse:0.263098\ttrain-rmse:0.252295\n",
+ "[215]\teval-rmse:0.263115\ttrain-rmse:0.252248\n",
+ "[216]\teval-rmse:0.263125\ttrain-rmse:0.252194\n",
+ "[217]\teval-rmse:0.263115\ttrain-rmse:0.252134\n",
+ "[218]\teval-rmse:0.263111\ttrain-rmse:0.252077\n",
+ "[219]\teval-rmse:0.263095\ttrain-rmse:0.252046\n",
+ "[220]\teval-rmse:0.263098\ttrain-rmse:0.252013\n",
+ "[221]\teval-rmse:0.26309\ttrain-rmse:0.251981\n",
+ "[222]\teval-rmse:0.263084\ttrain-rmse:0.251967\n",
+ "[223]\teval-rmse:0.263085\ttrain-rmse:0.251917\n",
+ "[224]\teval-rmse:0.263089\ttrain-rmse:0.251894\n",
+ "[225]\teval-rmse:0.26306\ttrain-rmse:0.251845\n",
+ "[226]\teval-rmse:0.263047\ttrain-rmse:0.251819\n",
+ "[227]\teval-rmse:0.263033\ttrain-rmse:0.251767\n",
+ "[228]\teval-rmse:0.263003\ttrain-rmse:0.251713\n",
+ "[229]\teval-rmse:0.263004\ttrain-rmse:0.251679\n",
+ "[230]\teval-rmse:0.263005\ttrain-rmse:0.251653\n",
+ "[231]\teval-rmse:0.263016\ttrain-rmse:0.25162\n",
+ "[232]\teval-rmse:0.263012\ttrain-rmse:0.251582\n",
+ "[233]\teval-rmse:0.26297\ttrain-rmse:0.251521\n",
+ "[234]\teval-rmse:0.262979\ttrain-rmse:0.251473\n",
+ "[235]\teval-rmse:0.262989\ttrain-rmse:0.251426\n",
+ "[236]\teval-rmse:0.262997\ttrain-rmse:0.25134\n",
+ "[237]\teval-rmse:0.263002\ttrain-rmse:0.251301\n",
+ "[238]\teval-rmse:0.263011\ttrain-rmse:0.251274\n",
+ "[239]\teval-rmse:0.263022\ttrain-rmse:0.251253\n",
+ "[240]\teval-rmse:0.263029\ttrain-rmse:0.251225\n",
+ "[241]\teval-rmse:0.263037\ttrain-rmse:0.251178\n",
+ "[242]\teval-rmse:0.263035\ttrain-rmse:0.251141\n",
+ "[243]\teval-rmse:0.263036\ttrain-rmse:0.251116\n",
+ "[244]\teval-rmse:0.263057\ttrain-rmse:0.251079\n",
+ "[245]\teval-rmse:0.263047\ttrain-rmse:0.251047\n",
+ "[246]\teval-rmse:0.263021\ttrain-rmse:0.250988\n",
+ "[247]\teval-rmse:0.26301\ttrain-rmse:0.250958\n",
+ "[248]\teval-rmse:0.263001\ttrain-rmse:0.250933\n",
+ "[249]\teval-rmse:0.263003\ttrain-rmse:0.25089\n",
+ "[250]\teval-rmse:0.263001\ttrain-rmse:0.250873\n",
+ "[251]\teval-rmse:0.262998\ttrain-rmse:0.250858\n",
+ "[252]\teval-rmse:0.262984\ttrain-rmse:0.250841\n",
+ "[253]\teval-rmse:0.262987\ttrain-rmse:0.250827\n",
+ "[254]\teval-rmse:0.26299\ttrain-rmse:0.250818\n",
+ "[255]\teval-rmse:0.262986\ttrain-rmse:0.250803\n",
+ "[256]\teval-rmse:0.263004\ttrain-rmse:0.250763\n",
+ "[257]\teval-rmse:0.262989\ttrain-rmse:0.250728\n",
+ "[258]\teval-rmse:0.262965\ttrain-rmse:0.250679\n",
+ "[259]\teval-rmse:0.262956\ttrain-rmse:0.25066\n",
+ "[260]\teval-rmse:0.262953\ttrain-rmse:0.250636\n",
+ "[261]\teval-rmse:0.262906\ttrain-rmse:0.250572\n",
+ "[262]\teval-rmse:0.262895\ttrain-rmse:0.250538\n",
+ "[263]\teval-rmse:0.262882\ttrain-rmse:0.250509\n",
+ "[264]\teval-rmse:0.262864\ttrain-rmse:0.250478\n",
+ "[265]\teval-rmse:0.262854\ttrain-rmse:0.250445\n",
+ "[266]\teval-rmse:0.262847\ttrain-rmse:0.250424\n",
+ "[267]\teval-rmse:0.262851\ttrain-rmse:0.250403\n",
+ "[268]\teval-rmse:0.262831\ttrain-rmse:0.250348\n",
+ "[269]\teval-rmse:0.262834\ttrain-rmse:0.250289\n",
+ "[270]\teval-rmse:0.262835\ttrain-rmse:0.250267\n",
+ "[271]\teval-rmse:0.262834\ttrain-rmse:0.25025\n",
+ "[272]\teval-rmse:0.262833\ttrain-rmse:0.250206\n",
+ "[273]\teval-rmse:0.262807\ttrain-rmse:0.250161\n",
+ "[274]\teval-rmse:0.262833\ttrain-rmse:0.250127\n",
+ "[275]\teval-rmse:0.262832\ttrain-rmse:0.250103\n",
+ "[276]\teval-rmse:0.262826\ttrain-rmse:0.250092\n",
+ "[277]\teval-rmse:0.262831\ttrain-rmse:0.250061\n",
+ "[278]\teval-rmse:0.26284\ttrain-rmse:0.250026\n",
+ "[279]\teval-rmse:0.262832\ttrain-rmse:0.250001\n",
+ "[280]\teval-rmse:0.262835\ttrain-rmse:0.249959\n",
+ "[281]\teval-rmse:0.262834\ttrain-rmse:0.249946\n",
+ "[282]\teval-rmse:0.262833\ttrain-rmse:0.249917\n",
+ "[283]\teval-rmse:0.262829\ttrain-rmse:0.249888\n",
+ "[284]\teval-rmse:0.262837\ttrain-rmse:0.249855\n",
+ "[285]\teval-rmse:0.262844\ttrain-rmse:0.249808\n",
+ "[286]\teval-rmse:0.262849\ttrain-rmse:0.249779\n",
+ "[287]\teval-rmse:0.262856\ttrain-rmse:0.249757\n",
+ "[288]\teval-rmse:0.26285\ttrain-rmse:0.249728\n",
+ "[289]\teval-rmse:0.262846\ttrain-rmse:0.249711\n",
+ "[290]\teval-rmse:0.262841\ttrain-rmse:0.249684\n",
+ "[291]\teval-rmse:0.262841\ttrain-rmse:0.249644\n",
+ "[292]\teval-rmse:0.262838\ttrain-rmse:0.249623\n",
+ "[293]\teval-rmse:0.262825\ttrain-rmse:0.249597\n",
+ "[294]\teval-rmse:0.262819\ttrain-rmse:0.24957\n",
+ "[295]\teval-rmse:0.262812\ttrain-rmse:0.249544\n",
+ "[296]\teval-rmse:0.262803\ttrain-rmse:0.249528\n",
+ "[297]\teval-rmse:0.2628\ttrain-rmse:0.249512\n",
+ "[298]\teval-rmse:0.262806\ttrain-rmse:0.249485\n",
+ "[299]\teval-rmse:0.262797\ttrain-rmse:0.249455\n",
+ "[300]\teval-rmse:0.262802\ttrain-rmse:0.249437\n",
+ "[301]\teval-rmse:0.262783\ttrain-rmse:0.249403\n",
+ "[302]\teval-rmse:0.262776\ttrain-rmse:0.249369\n",
+ "[303]\teval-rmse:0.262761\ttrain-rmse:0.249328\n",
+ "[304]\teval-rmse:0.262786\ttrain-rmse:0.249286\n",
+ "[305]\teval-rmse:0.262782\ttrain-rmse:0.24924\n",
+ "[306]\teval-rmse:0.262765\ttrain-rmse:0.249183\n",
+ "[307]\teval-rmse:0.262767\ttrain-rmse:0.24916\n",
+ "[308]\teval-rmse:0.262767\ttrain-rmse:0.249153\n",
+ "[309]\teval-rmse:0.262764\ttrain-rmse:0.24913\n",
+ "[310]\teval-rmse:0.262764\ttrain-rmse:0.249109\n",
+ "[311]\teval-rmse:0.262757\ttrain-rmse:0.249084\n",
+ "[312]\teval-rmse:0.26282\ttrain-rmse:0.249032\n",
+ "[313]\teval-rmse:0.262817\ttrain-rmse:0.249\n",
+ "[314]\teval-rmse:0.262807\ttrain-rmse:0.248963\n",
+ "[315]\teval-rmse:0.262787\ttrain-rmse:0.248914\n",
+ "[316]\teval-rmse:0.262772\ttrain-rmse:0.24888\n",
+ "[317]\teval-rmse:0.262766\ttrain-rmse:0.24884\n",
+ "[318]\teval-rmse:0.262744\ttrain-rmse:0.248782\n",
+ "[319]\teval-rmse:0.262748\ttrain-rmse:0.248764\n",
+ "[320]\teval-rmse:0.262775\ttrain-rmse:0.248718\n",
+ "[321]\teval-rmse:0.262761\ttrain-rmse:0.248686\n",
+ "[322]\teval-rmse:0.262766\ttrain-rmse:0.248649\n",
+ "[323]\teval-rmse:0.262768\ttrain-rmse:0.2486\n",
+ "[324]\teval-rmse:0.262784\ttrain-rmse:0.248564\n",
+ "[325]\teval-rmse:0.262794\ttrain-rmse:0.248535\n",
+ "[326]\teval-rmse:0.262783\ttrain-rmse:0.248509\n",
+ "[327]\teval-rmse:0.262778\ttrain-rmse:0.248497\n",
+ "[328]\teval-rmse:0.262767\ttrain-rmse:0.248473\n",
+ "[329]\teval-rmse:0.262769\ttrain-rmse:0.248456\n",
+ "[330]\teval-rmse:0.26278\ttrain-rmse:0.24842\n",
+ "[331]\teval-rmse:0.262797\ttrain-rmse:0.248394\n",
+ "[332]\teval-rmse:0.262803\ttrain-rmse:0.24837\n",
+ "[333]\teval-rmse:0.26281\ttrain-rmse:0.248353\n",
+ "[334]\teval-rmse:0.262814\ttrain-rmse:0.248322\n",
+ "[335]\teval-rmse:0.262813\ttrain-rmse:0.248301\n",
+ "[336]\teval-rmse:0.262812\ttrain-rmse:0.248287\n",
+ "[337]\teval-rmse:0.262809\ttrain-rmse:0.248265\n",
+ "[338]\teval-rmse:0.262798\ttrain-rmse:0.248227\n",
+ "[339]\teval-rmse:0.262793\ttrain-rmse:0.248196\n",
+ "[340]\teval-rmse:0.262818\ttrain-rmse:0.248158\n",
+ "[341]\teval-rmse:0.262822\ttrain-rmse:0.248136\n",
+ "[342]\teval-rmse:0.262817\ttrain-rmse:0.248122\n",
+ "[343]\teval-rmse:0.262817\ttrain-rmse:0.248109\n",
+ "[344]\teval-rmse:0.262807\ttrain-rmse:0.248086\n",
+ "[345]\teval-rmse:0.262791\ttrain-rmse:0.248058\n",
+ "[346]\teval-rmse:0.262781\ttrain-rmse:0.248031\n",
+ "[347]\teval-rmse:0.262792\ttrain-rmse:0.248002\n",
+ "[348]\teval-rmse:0.262788\ttrain-rmse:0.247978\n",
+ "[349]\teval-rmse:0.26278\ttrain-rmse:0.247967\n",
+ "[350]\teval-rmse:0.262799\ttrain-rmse:0.247933\n",
+ "[351]\teval-rmse:0.262791\ttrain-rmse:0.247884\n",
+ "[352]\teval-rmse:0.2628\ttrain-rmse:0.247844\n",
+ "[353]\teval-rmse:0.262816\ttrain-rmse:0.247819\n",
+ "[354]\teval-rmse:0.262837\ttrain-rmse:0.247781\n",
+ "[355]\teval-rmse:0.262844\ttrain-rmse:0.24776\n",
+ "[356]\teval-rmse:0.262837\ttrain-rmse:0.247742\n",
+ "[357]\teval-rmse:0.262847\ttrain-rmse:0.247726\n",
+ "[358]\teval-rmse:0.262844\ttrain-rmse:0.247718\n",
+ "[359]\teval-rmse:0.262858\ttrain-rmse:0.247687\n",
+ "[360]\teval-rmse:0.26287\ttrain-rmse:0.247648\n",
+ "[361]\teval-rmse:0.262868\ttrain-rmse:0.247631\n",
+ "[362]\teval-rmse:0.26287\ttrain-rmse:0.2476\n",
+ "[363]\teval-rmse:0.262861\ttrain-rmse:0.247557\n",
+ "[364]\teval-rmse:0.262849\ttrain-rmse:0.247522\n",
+ "[365]\teval-rmse:0.262858\ttrain-rmse:0.247499\n",
+ "[366]\teval-rmse:0.262859\ttrain-rmse:0.247466\n",
+ "[367]\teval-rmse:0.262878\ttrain-rmse:0.247447\n",
+ "[368]\teval-rmse:0.262857\ttrain-rmse:0.247432\n",
+ "[369]\teval-rmse:0.262854\ttrain-rmse:0.24741\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[370]\teval-rmse:0.262849\ttrain-rmse:0.247385\n",
+ "[371]\teval-rmse:0.262846\ttrain-rmse:0.247366\n",
+ "[372]\teval-rmse:0.262847\ttrain-rmse:0.247348\n",
+ "[373]\teval-rmse:0.262861\ttrain-rmse:0.247303\n",
+ "[374]\teval-rmse:0.262864\ttrain-rmse:0.247279\n",
+ "[375]\teval-rmse:0.262862\ttrain-rmse:0.247264\n",
+ "[376]\teval-rmse:0.262852\ttrain-rmse:0.247245\n",
+ "[377]\teval-rmse:0.262858\ttrain-rmse:0.247228\n",
+ "[378]\teval-rmse:0.26286\ttrain-rmse:0.247207\n",
+ "[379]\teval-rmse:0.262847\ttrain-rmse:0.247166\n",
+ "[380]\teval-rmse:0.262878\ttrain-rmse:0.247115\n",
+ "[381]\teval-rmse:0.262909\ttrain-rmse:0.247064\n",
+ "[382]\teval-rmse:0.262893\ttrain-rmse:0.247033\n",
+ "[383]\teval-rmse:0.262898\ttrain-rmse:0.247003\n",
+ "[384]\teval-rmse:0.262904\ttrain-rmse:0.246988\n",
+ "[385]\teval-rmse:0.262913\ttrain-rmse:0.246962\n",
+ "[386]\teval-rmse:0.262907\ttrain-rmse:0.246936\n",
+ "[387]\teval-rmse:0.262934\ttrain-rmse:0.246906\n",
+ "[388]\teval-rmse:0.262922\ttrain-rmse:0.246873\n",
+ "[389]\teval-rmse:0.262924\ttrain-rmse:0.246842\n",
+ "[390]\teval-rmse:0.262922\ttrain-rmse:0.246824\n",
+ "[391]\teval-rmse:0.262923\ttrain-rmse:0.246818\n",
+ "[392]\teval-rmse:0.262925\ttrain-rmse:0.246807\n",
+ "[393]\teval-rmse:0.262912\ttrain-rmse:0.246782\n",
+ "[394]\teval-rmse:0.262904\ttrain-rmse:0.246753\n",
+ "[395]\teval-rmse:0.262899\ttrain-rmse:0.246732\n",
+ "[396]\teval-rmse:0.262894\ttrain-rmse:0.246717\n",
+ "[397]\teval-rmse:0.262888\ttrain-rmse:0.246705\n",
+ "[398]\teval-rmse:0.262885\ttrain-rmse:0.246683\n",
+ "[399]\teval-rmse:0.262883\ttrain-rmse:0.246658\n",
+ "[400]\teval-rmse:0.262882\ttrain-rmse:0.24663\n",
+ "[401]\teval-rmse:0.262886\ttrain-rmse:0.246618\n",
+ "[402]\teval-rmse:0.262888\ttrain-rmse:0.246603\n",
+ "[403]\teval-rmse:0.262887\ttrain-rmse:0.246583\n",
+ "[404]\teval-rmse:0.262881\ttrain-rmse:0.246564\n",
+ "[405]\teval-rmse:0.26287\ttrain-rmse:0.246538\n",
+ "[406]\teval-rmse:0.262878\ttrain-rmse:0.24652\n",
+ "[407]\teval-rmse:0.262875\ttrain-rmse:0.246508\n",
+ "[408]\teval-rmse:0.26288\ttrain-rmse:0.246482\n",
+ "[409]\teval-rmse:0.26288\ttrain-rmse:0.246452\n",
+ "[410]\teval-rmse:0.262876\ttrain-rmse:0.246441\n",
+ "[411]\teval-rmse:0.26289\ttrain-rmse:0.246401\n",
+ "[412]\teval-rmse:0.262884\ttrain-rmse:0.24638\n",
+ "[413]\teval-rmse:0.262901\ttrain-rmse:0.246348\n",
+ "[414]\teval-rmse:0.262906\ttrain-rmse:0.246336\n",
+ "[415]\teval-rmse:0.262904\ttrain-rmse:0.246321\n",
+ "[416]\teval-rmse:0.262927\ttrain-rmse:0.246284\n",
+ "[417]\teval-rmse:0.262933\ttrain-rmse:0.246273\n",
+ "[418]\teval-rmse:0.262931\ttrain-rmse:0.24626\n",
+ "[419]\teval-rmse:0.262926\ttrain-rmse:0.246251\n",
+ "[420]\teval-rmse:0.262946\ttrain-rmse:0.246225\n",
+ "[421]\teval-rmse:0.262949\ttrain-rmse:0.246206\n",
+ "[422]\teval-rmse:0.262947\ttrain-rmse:0.246187\n",
+ "[423]\teval-rmse:0.262954\ttrain-rmse:0.246171\n",
+ "[424]\teval-rmse:0.262957\ttrain-rmse:0.246154\n",
+ "[425]\teval-rmse:0.262951\ttrain-rmse:0.246128\n",
+ "[426]\teval-rmse:0.262974\ttrain-rmse:0.246091\n",
+ "[427]\teval-rmse:0.262998\ttrain-rmse:0.246043\n",
+ "[428]\teval-rmse:0.262992\ttrain-rmse:0.246019\n",
+ "[429]\teval-rmse:0.262991\ttrain-rmse:0.246002\n",
+ "[430]\teval-rmse:0.26301\ttrain-rmse:0.245969\n",
+ "[431]\teval-rmse:0.263006\ttrain-rmse:0.245952\n",
+ "[432]\teval-rmse:0.263033\ttrain-rmse:0.245911\n",
+ "[433]\teval-rmse:0.263033\ttrain-rmse:0.245894\n",
+ "[434]\teval-rmse:0.262997\ttrain-rmse:0.245844\n",
+ "[435]\teval-rmse:0.262992\ttrain-rmse:0.245818\n",
+ "[436]\teval-rmse:0.262993\ttrain-rmse:0.245804\n",
+ "[437]\teval-rmse:0.262991\ttrain-rmse:0.24579\n",
+ "[438]\teval-rmse:0.262989\ttrain-rmse:0.245771\n",
+ "[439]\teval-rmse:0.262993\ttrain-rmse:0.245752\n",
+ "[440]\teval-rmse:0.262984\ttrain-rmse:0.245726\n",
+ "[441]\teval-rmse:0.26298\ttrain-rmse:0.245716\n",
+ "[442]\teval-rmse:0.262984\ttrain-rmse:0.245697\n",
+ "[443]\teval-rmse:0.262989\ttrain-rmse:0.245687\n",
+ "[444]\teval-rmse:0.263012\ttrain-rmse:0.24566\n",
+ "[445]\teval-rmse:0.263013\ttrain-rmse:0.245645\n",
+ "[446]\teval-rmse:0.263014\ttrain-rmse:0.245623\n",
+ "[447]\teval-rmse:0.263014\ttrain-rmse:0.245594\n",
+ "[448]\teval-rmse:0.263014\ttrain-rmse:0.245576\n",
+ "[449]\teval-rmse:0.263001\ttrain-rmse:0.245559\n",
+ "[450]\teval-rmse:0.263007\ttrain-rmse:0.245539\n",
+ "[451]\teval-rmse:0.26301\ttrain-rmse:0.245504\n",
+ "[452]\teval-rmse:0.26302\ttrain-rmse:0.245468\n",
+ "[453]\teval-rmse:0.263034\ttrain-rmse:0.245436\n",
+ "[454]\teval-rmse:0.263033\ttrain-rmse:0.245425\n",
+ "[455]\teval-rmse:0.26304\ttrain-rmse:0.245418\n",
+ "[456]\teval-rmse:0.263042\ttrain-rmse:0.245405\n",
+ "[457]\teval-rmse:0.263038\ttrain-rmse:0.245392\n",
+ "[458]\teval-rmse:0.263039\ttrain-rmse:0.245385\n",
+ "[459]\teval-rmse:0.26304\ttrain-rmse:0.24537\n",
+ "[460]\teval-rmse:0.263044\ttrain-rmse:0.245357\n",
+ "[461]\teval-rmse:0.263066\ttrain-rmse:0.245322\n",
+ "[462]\teval-rmse:0.26307\ttrain-rmse:0.245304\n",
+ "[463]\teval-rmse:0.263063\ttrain-rmse:0.245275\n",
+ "[464]\teval-rmse:0.263052\ttrain-rmse:0.245238\n",
+ "[465]\teval-rmse:0.263051\ttrain-rmse:0.245225\n",
+ "[466]\teval-rmse:0.263054\ttrain-rmse:0.245198\n",
+ "[467]\teval-rmse:0.263052\ttrain-rmse:0.245181\n",
+ "[468]\teval-rmse:0.263052\ttrain-rmse:0.245166\n",
+ "[469]\teval-rmse:0.263053\ttrain-rmse:0.245135\n",
+ "[470]\teval-rmse:0.263058\ttrain-rmse:0.245116\n",
+ "[471]\teval-rmse:0.263057\ttrain-rmse:0.245101\n",
+ "[472]\teval-rmse:0.263058\ttrain-rmse:0.245081\n",
+ "[473]\teval-rmse:0.263054\ttrain-rmse:0.245061\n",
+ "[474]\teval-rmse:0.263039\ttrain-rmse:0.245035\n",
+ "[475]\teval-rmse:0.26304\ttrain-rmse:0.24501\n",
+ "[476]\teval-rmse:0.263046\ttrain-rmse:0.244985\n",
+ "[477]\teval-rmse:0.263045\ttrain-rmse:0.244969\n",
+ "[478]\teval-rmse:0.263044\ttrain-rmse:0.244944\n",
+ "[479]\teval-rmse:0.263051\ttrain-rmse:0.24491\n",
+ "[480]\teval-rmse:0.263057\ttrain-rmse:0.244898\n",
+ "[481]\teval-rmse:0.263063\ttrain-rmse:0.244883\n",
+ "[482]\teval-rmse:0.263067\ttrain-rmse:0.244871\n",
+ "[483]\teval-rmse:0.263046\ttrain-rmse:0.24483\n",
+ "[484]\teval-rmse:0.263036\ttrain-rmse:0.244783\n",
+ "[485]\teval-rmse:0.263035\ttrain-rmse:0.244765\n",
+ "[486]\teval-rmse:0.263034\ttrain-rmse:0.244744\n",
+ "[487]\teval-rmse:0.263042\ttrain-rmse:0.244717\n",
+ "[488]\teval-rmse:0.263033\ttrain-rmse:0.244695\n",
+ "[489]\teval-rmse:0.263058\ttrain-rmse:0.244677\n",
+ "[490]\teval-rmse:0.263061\ttrain-rmse:0.244652\n",
+ "[491]\teval-rmse:0.263059\ttrain-rmse:0.244632\n",
+ "[492]\teval-rmse:0.263064\ttrain-rmse:0.244614\n",
+ "[493]\teval-rmse:0.263073\ttrain-rmse:0.244582\n",
+ "[494]\teval-rmse:0.26309\ttrain-rmse:0.244544\n",
+ "[495]\teval-rmse:0.263093\ttrain-rmse:0.244517\n",
+ "[496]\teval-rmse:0.263086\ttrain-rmse:0.24449\n",
+ "[497]\teval-rmse:0.263105\ttrain-rmse:0.244459\n",
+ "[498]\teval-rmse:0.263111\ttrain-rmse:0.244435\n",
+ "[499]\teval-rmse:0.263111\ttrain-rmse:0.244403\n",
+ "[500]\teval-rmse:0.263118\ttrain-rmse:0.244382\n",
+ "[501]\teval-rmse:0.263106\ttrain-rmse:0.244348\n",
+ "[502]\teval-rmse:0.263092\ttrain-rmse:0.244331\n",
+ "[503]\teval-rmse:0.26309\ttrain-rmse:0.244314\n",
+ "[504]\teval-rmse:0.263106\ttrain-rmse:0.244283\n",
+ "[505]\teval-rmse:0.263097\ttrain-rmse:0.24427\n",
+ "[506]\teval-rmse:0.263121\ttrain-rmse:0.244243\n",
+ "[507]\teval-rmse:0.263121\ttrain-rmse:0.244235\n",
+ "[508]\teval-rmse:0.263116\ttrain-rmse:0.244229\n",
+ "[509]\teval-rmse:0.263117\ttrain-rmse:0.244217\n",
+ "[510]\teval-rmse:0.263127\ttrain-rmse:0.244206\n",
+ "[511]\teval-rmse:0.263138\ttrain-rmse:0.244182\n",
+ "[512]\teval-rmse:0.263137\ttrain-rmse:0.244172\n",
+ "[513]\teval-rmse:0.26313\ttrain-rmse:0.244132\n",
+ "[514]\teval-rmse:0.263125\ttrain-rmse:0.244103\n",
+ "[515]\teval-rmse:0.263127\ttrain-rmse:0.244089\n",
+ "[516]\teval-rmse:0.26313\ttrain-rmse:0.244055\n",
+ "[517]\teval-rmse:0.263132\ttrain-rmse:0.244031\n",
+ "[518]\teval-rmse:0.263149\ttrain-rmse:0.243999\n",
+ "[519]\teval-rmse:0.263164\ttrain-rmse:0.243967\n",
+ "[520]\teval-rmse:0.26316\ttrain-rmse:0.243945\n",
+ "[521]\teval-rmse:0.263169\ttrain-rmse:0.24393\n",
+ "[522]\teval-rmse:0.263164\ttrain-rmse:0.243909\n",
+ "[523]\teval-rmse:0.263165\ttrain-rmse:0.243897\n",
+ "[524]\teval-rmse:0.263172\ttrain-rmse:0.243876\n",
+ "[525]\teval-rmse:0.263171\ttrain-rmse:0.243848\n",
+ "[526]\teval-rmse:0.263163\ttrain-rmse:0.243815\n",
+ "[527]\teval-rmse:0.263149\ttrain-rmse:0.24378\n",
+ "[528]\teval-rmse:0.263157\ttrain-rmse:0.243754\n",
+ "[529]\teval-rmse:0.263154\ttrain-rmse:0.243743\n",
+ "[530]\teval-rmse:0.263156\ttrain-rmse:0.243724\n",
+ "[531]\teval-rmse:0.263157\ttrain-rmse:0.243708\n",
+ "[532]\teval-rmse:0.263157\ttrain-rmse:0.243685\n",
+ "[533]\teval-rmse:0.263149\ttrain-rmse:0.243656\n",
+ "[534]\teval-rmse:0.263152\ttrain-rmse:0.243647\n",
+ "[535]\teval-rmse:0.263172\ttrain-rmse:0.243616\n",
+ "[536]\teval-rmse:0.263167\ttrain-rmse:0.243607\n",
+ "[537]\teval-rmse:0.263162\ttrain-rmse:0.2436\n",
+ "[538]\teval-rmse:0.263154\ttrain-rmse:0.243577\n",
+ "[539]\teval-rmse:0.263161\ttrain-rmse:0.243564\n",
+ "[540]\teval-rmse:0.263164\ttrain-rmse:0.24355\n",
+ "[541]\teval-rmse:0.263163\ttrain-rmse:0.243525\n",
+ "[542]\teval-rmse:0.263166\ttrain-rmse:0.243498\n",
+ "[543]\teval-rmse:0.263182\ttrain-rmse:0.24347\n",
+ "[544]\teval-rmse:0.263187\ttrain-rmse:0.243442\n",
+ "[545]\teval-rmse:0.26319\ttrain-rmse:0.243417\n",
+ "[546]\teval-rmse:0.263184\ttrain-rmse:0.243386\n",
+ "[547]\teval-rmse:0.263184\ttrain-rmse:0.243362\n",
+ "[548]\teval-rmse:0.263175\ttrain-rmse:0.243342\n",
+ "[549]\teval-rmse:0.263181\ttrain-rmse:0.243321\n",
+ "[550]\teval-rmse:0.263193\ttrain-rmse:0.243302\n",
+ "[551]\teval-rmse:0.263198\ttrain-rmse:0.243277\n",
+ "[552]\teval-rmse:0.263196\ttrain-rmse:0.243251\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[553]\teval-rmse:0.263194\ttrain-rmse:0.243224\n",
+ "[554]\teval-rmse:0.263191\ttrain-rmse:0.243197\n",
+ "[555]\teval-rmse:0.263188\ttrain-rmse:0.243174\n",
+ "[556]\teval-rmse:0.263187\ttrain-rmse:0.243154\n",
+ "[557]\teval-rmse:0.263199\ttrain-rmse:0.243133\n",
+ "[558]\teval-rmse:0.263191\ttrain-rmse:0.243114\n",
+ "[559]\teval-rmse:0.263191\ttrain-rmse:0.243106\n",
+ "[560]\teval-rmse:0.263241\ttrain-rmse:0.243067\n",
+ "[561]\teval-rmse:0.263241\ttrain-rmse:0.243043\n",
+ "[562]\teval-rmse:0.263239\ttrain-rmse:0.243027\n",
+ "[563]\teval-rmse:0.263241\ttrain-rmse:0.243009\n",
+ "[564]\teval-rmse:0.263247\ttrain-rmse:0.242986\n",
+ "[565]\teval-rmse:0.263253\ttrain-rmse:0.242969\n",
+ "[566]\teval-rmse:0.263255\ttrain-rmse:0.242948\n",
+ "[567]\teval-rmse:0.263259\ttrain-rmse:0.24292\n",
+ "[568]\teval-rmse:0.263261\ttrain-rmse:0.242895\n",
+ "[569]\teval-rmse:0.26327\ttrain-rmse:0.24287\n",
+ "[570]\teval-rmse:0.263266\ttrain-rmse:0.242843\n",
+ "[571]\teval-rmse:0.263266\ttrain-rmse:0.242826\n",
+ "[572]\teval-rmse:0.263299\ttrain-rmse:0.242794\n",
+ "[573]\teval-rmse:0.263301\ttrain-rmse:0.242772\n",
+ "[574]\teval-rmse:0.26331\ttrain-rmse:0.24275\n",
+ "[575]\teval-rmse:0.263302\ttrain-rmse:0.242722\n",
+ "[576]\teval-rmse:0.263303\ttrain-rmse:0.242702\n",
+ "[577]\teval-rmse:0.263296\ttrain-rmse:0.24268\n",
+ "[578]\teval-rmse:0.263303\ttrain-rmse:0.242659\n",
+ "[579]\teval-rmse:0.263313\ttrain-rmse:0.242636\n",
+ "[580]\teval-rmse:0.263309\ttrain-rmse:0.242625\n",
+ "[581]\teval-rmse:0.26331\ttrain-rmse:0.242607\n",
+ "[582]\teval-rmse:0.263308\ttrain-rmse:0.242593\n",
+ "[583]\teval-rmse:0.263301\ttrain-rmse:0.242573\n",
+ "[584]\teval-rmse:0.263313\ttrain-rmse:0.242544\n",
+ "[585]\teval-rmse:0.263315\ttrain-rmse:0.242531\n",
+ "[586]\teval-rmse:0.263329\ttrain-rmse:0.242511\n",
+ "[587]\teval-rmse:0.263331\ttrain-rmse:0.242497\n",
+ "[588]\teval-rmse:0.263338\ttrain-rmse:0.242484\n",
+ "[589]\teval-rmse:0.263341\ttrain-rmse:0.242471\n",
+ "[590]\teval-rmse:0.263339\ttrain-rmse:0.242463\n",
+ "[591]\teval-rmse:0.263336\ttrain-rmse:0.242448\n",
+ "[592]\teval-rmse:0.263331\ttrain-rmse:0.242438\n",
+ "[593]\teval-rmse:0.263326\ttrain-rmse:0.242432\n",
+ "[594]\teval-rmse:0.263323\ttrain-rmse:0.242417\n",
+ "[595]\teval-rmse:0.263311\ttrain-rmse:0.242392\n",
+ "[596]\teval-rmse:0.263313\ttrain-rmse:0.242383\n",
+ "[597]\teval-rmse:0.263309\ttrain-rmse:0.242368\n",
+ "[598]\teval-rmse:0.263315\ttrain-rmse:0.24235\n",
+ "[599]\teval-rmse:0.26332\ttrain-rmse:0.242334\n",
+ "[600]\teval-rmse:0.263315\ttrain-rmse:0.242313\n",
+ "[601]\teval-rmse:0.263315\ttrain-rmse:0.242299\n",
+ "[602]\teval-rmse:0.263314\ttrain-rmse:0.242278\n",
+ "[603]\teval-rmse:0.263317\ttrain-rmse:0.242262\n",
+ "[604]\teval-rmse:0.263316\ttrain-rmse:0.242232\n",
+ "[605]\teval-rmse:0.263336\ttrain-rmse:0.242196\n",
+ "[606]\teval-rmse:0.263334\ttrain-rmse:0.242181\n",
+ "[607]\teval-rmse:0.263328\ttrain-rmse:0.242155\n",
+ "[608]\teval-rmse:0.263333\ttrain-rmse:0.242139\n",
+ "[609]\teval-rmse:0.263331\ttrain-rmse:0.242124\n",
+ "[610]\teval-rmse:0.263332\ttrain-rmse:0.242115\n",
+ "[611]\teval-rmse:0.263332\ttrain-rmse:0.242094\n",
+ "[612]\teval-rmse:0.263328\ttrain-rmse:0.242066\n",
+ "[613]\teval-rmse:0.263324\ttrain-rmse:0.242043\n",
+ "[614]\teval-rmse:0.263336\ttrain-rmse:0.24202\n",
+ "[615]\teval-rmse:0.263343\ttrain-rmse:0.242001\n",
+ "[616]\teval-rmse:0.26334\ttrain-rmse:0.241986\n",
+ "[617]\teval-rmse:0.263332\ttrain-rmse:0.241957\n",
+ "[618]\teval-rmse:0.263328\ttrain-rmse:0.241944\n",
+ "[619]\teval-rmse:0.263329\ttrain-rmse:0.241924\n",
+ "[620]\teval-rmse:0.263353\ttrain-rmse:0.241896\n",
+ "[621]\teval-rmse:0.26335\ttrain-rmse:0.241882\n",
+ "[622]\teval-rmse:0.263344\ttrain-rmse:0.241865\n",
+ "[623]\teval-rmse:0.263345\ttrain-rmse:0.241844\n",
+ "[624]\teval-rmse:0.263342\ttrain-rmse:0.241822\n",
+ "[625]\teval-rmse:0.263343\ttrain-rmse:0.241804\n",
+ "[626]\teval-rmse:0.263331\ttrain-rmse:0.241785\n",
+ "[627]\teval-rmse:0.263333\ttrain-rmse:0.24177\n",
+ "[628]\teval-rmse:0.26333\ttrain-rmse:0.241752\n",
+ "[629]\teval-rmse:0.263332\ttrain-rmse:0.241745\n",
+ "[630]\teval-rmse:0.263332\ttrain-rmse:0.241736\n",
+ "[631]\teval-rmse:0.263333\ttrain-rmse:0.241722\n",
+ "[632]\teval-rmse:0.263344\ttrain-rmse:0.241699\n",
+ "[633]\teval-rmse:0.263354\ttrain-rmse:0.241675\n",
+ "[634]\teval-rmse:0.263367\ttrain-rmse:0.241653\n",
+ "[635]\teval-rmse:0.263366\ttrain-rmse:0.241647\n",
+ "[636]\teval-rmse:0.263371\ttrain-rmse:0.24163\n",
+ "[637]\teval-rmse:0.263374\ttrain-rmse:0.241614\n",
+ "[638]\teval-rmse:0.263376\ttrain-rmse:0.241599\n",
+ "[639]\teval-rmse:0.263377\ttrain-rmse:0.24159\n",
+ "[640]\teval-rmse:0.263374\ttrain-rmse:0.241577\n",
+ "[641]\teval-rmse:0.263382\ttrain-rmse:0.241549\n",
+ "[642]\teval-rmse:0.263383\ttrain-rmse:0.241535\n",
+ "[643]\teval-rmse:0.263388\ttrain-rmse:0.241504\n",
+ "[644]\teval-rmse:0.263385\ttrain-rmse:0.241485\n",
+ "[645]\teval-rmse:0.263383\ttrain-rmse:0.241472\n",
+ "[646]\teval-rmse:0.263383\ttrain-rmse:0.241463\n",
+ "[647]\teval-rmse:0.263386\ttrain-rmse:0.241452\n",
+ "[648]\teval-rmse:0.263376\ttrain-rmse:0.241437\n",
+ "[649]\teval-rmse:0.26338\ttrain-rmse:0.241424\n",
+ "[650]\teval-rmse:0.263386\ttrain-rmse:0.241412\n",
+ "[651]\teval-rmse:0.263389\ttrain-rmse:0.241392\n",
+ "[652]\teval-rmse:0.263386\ttrain-rmse:0.241373\n",
+ "[653]\teval-rmse:0.263392\ttrain-rmse:0.241353\n",
+ "[654]\teval-rmse:0.263389\ttrain-rmse:0.241326\n",
+ "[655]\teval-rmse:0.263383\ttrain-rmse:0.241308\n",
+ "[656]\teval-rmse:0.263384\ttrain-rmse:0.241286\n",
+ "[657]\teval-rmse:0.263384\ttrain-rmse:0.24127\n",
+ "[658]\teval-rmse:0.263381\ttrain-rmse:0.241253\n",
+ "[659]\teval-rmse:0.26338\ttrain-rmse:0.241243\n",
+ "[660]\teval-rmse:0.263376\ttrain-rmse:0.241238\n",
+ "[661]\teval-rmse:0.263372\ttrain-rmse:0.241224\n",
+ "[662]\teval-rmse:0.263373\ttrain-rmse:0.241208\n",
+ "[663]\teval-rmse:0.26338\ttrain-rmse:0.241195\n",
+ "[664]\teval-rmse:0.263381\ttrain-rmse:0.241176\n",
+ "[665]\teval-rmse:0.263385\ttrain-rmse:0.241154\n",
+ "[666]\teval-rmse:0.263385\ttrain-rmse:0.241142\n",
+ "[667]\teval-rmse:0.263387\ttrain-rmse:0.241128\n",
+ "[668]\teval-rmse:0.263394\ttrain-rmse:0.241117\n",
+ "[669]\teval-rmse:0.263395\ttrain-rmse:0.241103\n",
+ "[670]\teval-rmse:0.263416\ttrain-rmse:0.241074\n",
+ "[671]\teval-rmse:0.263415\ttrain-rmse:0.241063\n",
+ "[672]\teval-rmse:0.263425\ttrain-rmse:0.241034\n",
+ "[673]\teval-rmse:0.263424\ttrain-rmse:0.241018\n",
+ "[674]\teval-rmse:0.263452\ttrain-rmse:0.240987\n",
+ "[675]\teval-rmse:0.263456\ttrain-rmse:0.24097\n",
+ "[676]\teval-rmse:0.263452\ttrain-rmse:0.240956\n",
+ "[677]\teval-rmse:0.263448\ttrain-rmse:0.240937\n",
+ "[678]\teval-rmse:0.263452\ttrain-rmse:0.240908\n",
+ "[679]\teval-rmse:0.263455\ttrain-rmse:0.240898\n",
+ "[680]\teval-rmse:0.263454\ttrain-rmse:0.240891\n",
+ "[681]\teval-rmse:0.263451\ttrain-rmse:0.240879\n",
+ "[682]\teval-rmse:0.263453\ttrain-rmse:0.240862\n",
+ "[683]\teval-rmse:0.263453\ttrain-rmse:0.240845\n",
+ "[684]\teval-rmse:0.263453\ttrain-rmse:0.240821\n",
+ "[685]\teval-rmse:0.263436\ttrain-rmse:0.240795\n",
+ "[686]\teval-rmse:0.263442\ttrain-rmse:0.240779\n",
+ "[687]\teval-rmse:0.263448\ttrain-rmse:0.240758\n",
+ "[688]\teval-rmse:0.26346\ttrain-rmse:0.240734\n",
+ "[689]\teval-rmse:0.263451\ttrain-rmse:0.240714\n",
+ "[690]\teval-rmse:0.263453\ttrain-rmse:0.240688\n",
+ "[691]\teval-rmse:0.26345\ttrain-rmse:0.240675\n",
+ "[692]\teval-rmse:0.263451\ttrain-rmse:0.240666\n",
+ "[693]\teval-rmse:0.263467\ttrain-rmse:0.240652\n",
+ "[694]\teval-rmse:0.263471\ttrain-rmse:0.240641\n",
+ "[695]\teval-rmse:0.263478\ttrain-rmse:0.240614\n",
+ "[696]\teval-rmse:0.263474\ttrain-rmse:0.240595\n",
+ "[697]\teval-rmse:0.263467\ttrain-rmse:0.24058\n",
+ "[698]\teval-rmse:0.263465\ttrain-rmse:0.24056\n",
+ "[699]\teval-rmse:0.263462\ttrain-rmse:0.240548\n",
+ "[700]\teval-rmse:0.263461\ttrain-rmse:0.240531\n",
+ "[701]\teval-rmse:0.263468\ttrain-rmse:0.240517\n",
+ "[702]\teval-rmse:0.263473\ttrain-rmse:0.240501\n",
+ "[703]\teval-rmse:0.263478\ttrain-rmse:0.240494\n",
+ "[704]\teval-rmse:0.263482\ttrain-rmse:0.240482\n",
+ "[705]\teval-rmse:0.263478\ttrain-rmse:0.240462\n",
+ "[706]\teval-rmse:0.263476\ttrain-rmse:0.240438\n",
+ "[707]\teval-rmse:0.263486\ttrain-rmse:0.240423\n",
+ "[708]\teval-rmse:0.26349\ttrain-rmse:0.240411\n",
+ "[709]\teval-rmse:0.263482\ttrain-rmse:0.240389\n",
+ "[710]\teval-rmse:0.263481\ttrain-rmse:0.240379\n",
+ "[711]\teval-rmse:0.26348\ttrain-rmse:0.240366\n",
+ "[712]\teval-rmse:0.263469\ttrain-rmse:0.240344\n",
+ "[713]\teval-rmse:0.263459\ttrain-rmse:0.240328\n",
+ "[714]\teval-rmse:0.26346\ttrain-rmse:0.240309\n",
+ "[715]\teval-rmse:0.263465\ttrain-rmse:0.240288\n",
+ "[716]\teval-rmse:0.263463\ttrain-rmse:0.240275\n",
+ "[717]\teval-rmse:0.263464\ttrain-rmse:0.240257\n",
+ "[718]\teval-rmse:0.263462\ttrain-rmse:0.240251\n",
+ "[719]\teval-rmse:0.263459\ttrain-rmse:0.240238\n",
+ "[720]\teval-rmse:0.263456\ttrain-rmse:0.240218\n",
+ "[721]\teval-rmse:0.263455\ttrain-rmse:0.240208\n",
+ "[722]\teval-rmse:0.263456\ttrain-rmse:0.240197\n",
+ "[723]\teval-rmse:0.263452\ttrain-rmse:0.24019\n",
+ "[724]\teval-rmse:0.263454\ttrain-rmse:0.240181\n",
+ "[725]\teval-rmse:0.263453\ttrain-rmse:0.240174\n",
+ "[726]\teval-rmse:0.26346\ttrain-rmse:0.240162\n",
+ "[727]\teval-rmse:0.263457\ttrain-rmse:0.240154\n",
+ "[728]\teval-rmse:0.263456\ttrain-rmse:0.240151\n",
+ "[729]\teval-rmse:0.263456\ttrain-rmse:0.240138\n",
+ "[730]\teval-rmse:0.263451\ttrain-rmse:0.240129\n",
+ "[731]\teval-rmse:0.263458\ttrain-rmse:0.240116\n",
+ "[732]\teval-rmse:0.263468\ttrain-rmse:0.240089\n",
+ "[733]\teval-rmse:0.263465\ttrain-rmse:0.240078\n",
+ "[734]\teval-rmse:0.26347\ttrain-rmse:0.240054\n",
+ "[735]\teval-rmse:0.263469\ttrain-rmse:0.24003\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[736]\teval-rmse:0.263484\ttrain-rmse:0.240008\n",
+ "[737]\teval-rmse:0.263492\ttrain-rmse:0.239993\n",
+ "[738]\teval-rmse:0.263497\ttrain-rmse:0.239974\n",
+ "[739]\teval-rmse:0.263497\ttrain-rmse:0.239949\n",
+ "[740]\teval-rmse:0.263519\ttrain-rmse:0.239935\n",
+ "[741]\teval-rmse:0.263518\ttrain-rmse:0.239926\n",
+ "[742]\teval-rmse:0.263518\ttrain-rmse:0.239921\n",
+ "[743]\teval-rmse:0.263518\ttrain-rmse:0.239917\n",
+ "[744]\teval-rmse:0.263509\ttrain-rmse:0.239895\n",
+ "[745]\teval-rmse:0.263515\ttrain-rmse:0.239886\n",
+ "[746]\teval-rmse:0.263511\ttrain-rmse:0.23987\n",
+ "[747]\teval-rmse:0.263525\ttrain-rmse:0.239848\n",
+ "[748]\teval-rmse:0.263523\ttrain-rmse:0.23983\n",
+ "[749]\teval-rmse:0.26353\ttrain-rmse:0.239813\n",
+ "[750]\teval-rmse:0.263533\ttrain-rmse:0.239788\n",
+ "[751]\teval-rmse:0.263542\ttrain-rmse:0.239781\n",
+ "[752]\teval-rmse:0.263544\ttrain-rmse:0.239768\n",
+ "[753]\teval-rmse:0.263546\ttrain-rmse:0.239754\n",
+ "[754]\teval-rmse:0.263545\ttrain-rmse:0.239735\n",
+ "[755]\teval-rmse:0.263547\ttrain-rmse:0.239722\n",
+ "[756]\teval-rmse:0.263549\ttrain-rmse:0.239703\n",
+ "[757]\teval-rmse:0.26354\ttrain-rmse:0.239683\n",
+ "[758]\teval-rmse:0.263536\ttrain-rmse:0.239671\n",
+ "[759]\teval-rmse:0.263532\ttrain-rmse:0.239656\n",
+ "[760]\teval-rmse:0.263531\ttrain-rmse:0.239651\n",
+ "[761]\teval-rmse:0.263535\ttrain-rmse:0.239629\n",
+ "[762]\teval-rmse:0.263537\ttrain-rmse:0.239612\n",
+ "[763]\teval-rmse:0.263546\ttrain-rmse:0.239599\n",
+ "[764]\teval-rmse:0.263548\ttrain-rmse:0.239577\n",
+ "[765]\teval-rmse:0.263545\ttrain-rmse:0.239563\n",
+ "[766]\teval-rmse:0.263546\ttrain-rmse:0.239553\n",
+ "[767]\teval-rmse:0.263536\ttrain-rmse:0.239535\n",
+ "[768]\teval-rmse:0.263534\ttrain-rmse:0.239528\n",
+ "[769]\teval-rmse:0.263539\ttrain-rmse:0.23952\n",
+ "[770]\teval-rmse:0.263537\ttrain-rmse:0.239508\n",
+ "[771]\teval-rmse:0.263536\ttrain-rmse:0.239492\n",
+ "[772]\teval-rmse:0.263536\ttrain-rmse:0.239481\n",
+ "[773]\teval-rmse:0.26353\ttrain-rmse:0.239462\n",
+ "[774]\teval-rmse:0.263533\ttrain-rmse:0.239443\n",
+ "[775]\teval-rmse:0.263533\ttrain-rmse:0.239431\n",
+ "[776]\teval-rmse:0.263544\ttrain-rmse:0.239413\n",
+ "[777]\teval-rmse:0.263545\ttrain-rmse:0.239401\n",
+ "[778]\teval-rmse:0.263547\ttrain-rmse:0.239394\n",
+ "[779]\teval-rmse:0.263554\ttrain-rmse:0.239387\n",
+ "[780]\teval-rmse:0.263561\ttrain-rmse:0.239371\n",
+ "[781]\teval-rmse:0.263561\ttrain-rmse:0.239342\n",
+ "[782]\teval-rmse:0.263574\ttrain-rmse:0.239324\n",
+ "[783]\teval-rmse:0.263573\ttrain-rmse:0.239316\n",
+ "[784]\teval-rmse:0.263572\ttrain-rmse:0.239298\n",
+ "[785]\teval-rmse:0.263579\ttrain-rmse:0.239279\n",
+ "[786]\teval-rmse:0.263583\ttrain-rmse:0.239265\n",
+ "[787]\teval-rmse:0.263589\ttrain-rmse:0.239235\n",
+ "[788]\teval-rmse:0.263609\ttrain-rmse:0.239208\n",
+ "[789]\teval-rmse:0.263611\ttrain-rmse:0.239197\n",
+ "[790]\teval-rmse:0.263611\ttrain-rmse:0.239172\n",
+ "[791]\teval-rmse:0.263624\ttrain-rmse:0.239154\n",
+ "[792]\teval-rmse:0.263621\ttrain-rmse:0.239138\n",
+ "[793]\teval-rmse:0.263629\ttrain-rmse:0.239114\n",
+ "[794]\teval-rmse:0.26364\ttrain-rmse:0.239091\n",
+ "[795]\teval-rmse:0.263642\ttrain-rmse:0.239079\n",
+ "[796]\teval-rmse:0.263647\ttrain-rmse:0.23906\n",
+ "[797]\teval-rmse:0.263643\ttrain-rmse:0.239046\n",
+ "[798]\teval-rmse:0.263645\ttrain-rmse:0.239035\n",
+ "[799]\teval-rmse:0.263648\ttrain-rmse:0.239015\n",
+ "[800]\teval-rmse:0.263651\ttrain-rmse:0.239006\n",
+ "[801]\teval-rmse:0.263643\ttrain-rmse:0.238993\n",
+ "[802]\teval-rmse:0.263641\ttrain-rmse:0.238981\n",
+ "[803]\teval-rmse:0.263651\ttrain-rmse:0.238968\n",
+ "[804]\teval-rmse:0.263651\ttrain-rmse:0.238952\n",
+ "[805]\teval-rmse:0.26366\ttrain-rmse:0.23894\n",
+ "[806]\teval-rmse:0.263668\ttrain-rmse:0.238926\n",
+ "[807]\teval-rmse:0.263668\ttrain-rmse:0.23891\n",
+ "[808]\teval-rmse:0.263677\ttrain-rmse:0.2389\n",
+ "[809]\teval-rmse:0.263676\ttrain-rmse:0.238887\n",
+ "[810]\teval-rmse:0.263669\ttrain-rmse:0.238876\n",
+ "[811]\teval-rmse:0.263675\ttrain-rmse:0.238864\n",
+ "[812]\teval-rmse:0.263684\ttrain-rmse:0.238854\n",
+ "[813]\teval-rmse:0.263689\ttrain-rmse:0.238841\n",
+ "[814]\teval-rmse:0.263698\ttrain-rmse:0.238827\n",
+ "[815]\teval-rmse:0.263701\ttrain-rmse:0.238809\n",
+ "[816]\teval-rmse:0.263703\ttrain-rmse:0.23879\n",
+ "[817]\teval-rmse:0.263707\ttrain-rmse:0.238781\n",
+ "[818]\teval-rmse:0.263705\ttrain-rmse:0.238774\n",
+ "[819]\teval-rmse:0.263706\ttrain-rmse:0.238767\n",
+ "[820]\teval-rmse:0.263705\ttrain-rmse:0.238746\n",
+ "[821]\teval-rmse:0.263704\ttrain-rmse:0.238731\n",
+ "[822]\teval-rmse:0.263702\ttrain-rmse:0.238705\n",
+ "[823]\teval-rmse:0.2637\ttrain-rmse:0.238687\n",
+ "[824]\teval-rmse:0.263696\ttrain-rmse:0.23867\n",
+ "[825]\teval-rmse:0.263697\ttrain-rmse:0.238656\n",
+ "[826]\teval-rmse:0.263713\ttrain-rmse:0.238633\n",
+ "[827]\teval-rmse:0.263721\ttrain-rmse:0.238613\n",
+ "[828]\teval-rmse:0.263723\ttrain-rmse:0.238604\n",
+ "[829]\teval-rmse:0.263721\ttrain-rmse:0.238592\n",
+ "[830]\teval-rmse:0.263718\ttrain-rmse:0.238572\n",
+ "[831]\teval-rmse:0.263717\ttrain-rmse:0.238563\n",
+ "[832]\teval-rmse:0.26372\ttrain-rmse:0.238548\n",
+ "[833]\teval-rmse:0.263724\ttrain-rmse:0.238535\n",
+ "[834]\teval-rmse:0.263726\ttrain-rmse:0.238524\n",
+ "[835]\teval-rmse:0.263729\ttrain-rmse:0.23851\n",
+ "[836]\teval-rmse:0.26373\ttrain-rmse:0.238502\n",
+ "[837]\teval-rmse:0.26373\ttrain-rmse:0.238492\n",
+ "[838]\teval-rmse:0.263738\ttrain-rmse:0.238474\n",
+ "[839]\teval-rmse:0.26375\ttrain-rmse:0.238443\n",
+ "[840]\teval-rmse:0.263748\ttrain-rmse:0.238427\n",
+ "[841]\teval-rmse:0.26375\ttrain-rmse:0.238422\n",
+ "[842]\teval-rmse:0.263749\ttrain-rmse:0.238416\n",
+ "[843]\teval-rmse:0.263756\ttrain-rmse:0.238402\n",
+ "[844]\teval-rmse:0.263784\ttrain-rmse:0.238369\n",
+ "[845]\teval-rmse:0.263784\ttrain-rmse:0.238365\n",
+ "[846]\teval-rmse:0.26379\ttrain-rmse:0.238347\n",
+ "[847]\teval-rmse:0.263788\ttrain-rmse:0.23833\n",
+ "[848]\teval-rmse:0.26379\ttrain-rmse:0.238315\n",
+ "[849]\teval-rmse:0.263786\ttrain-rmse:0.238297\n",
+ "[850]\teval-rmse:0.263795\ttrain-rmse:0.238287\n",
+ "[851]\teval-rmse:0.263791\ttrain-rmse:0.238277\n",
+ "[852]\teval-rmse:0.263795\ttrain-rmse:0.238269\n",
+ "[853]\teval-rmse:0.263801\ttrain-rmse:0.238258\n",
+ "[854]\teval-rmse:0.263796\ttrain-rmse:0.238249\n",
+ "[855]\teval-rmse:0.2638\ttrain-rmse:0.238228\n",
+ "[856]\teval-rmse:0.2638\ttrain-rmse:0.238221\n",
+ "[857]\teval-rmse:0.263793\ttrain-rmse:0.238215\n",
+ "[858]\teval-rmse:0.263799\ttrain-rmse:0.238208\n",
+ "[859]\teval-rmse:0.263794\ttrain-rmse:0.23819\n",
+ "[860]\teval-rmse:0.263792\ttrain-rmse:0.238175\n",
+ "[861]\teval-rmse:0.263797\ttrain-rmse:0.238157\n",
+ "[862]\teval-rmse:0.263796\ttrain-rmse:0.238148\n",
+ "[863]\teval-rmse:0.263799\ttrain-rmse:0.238137\n",
+ "[864]\teval-rmse:0.2638\ttrain-rmse:0.238126\n",
+ "[865]\teval-rmse:0.263799\ttrain-rmse:0.238115\n",
+ "[866]\teval-rmse:0.263806\ttrain-rmse:0.238101\n",
+ "[867]\teval-rmse:0.263807\ttrain-rmse:0.238084\n",
+ "[868]\teval-rmse:0.263814\ttrain-rmse:0.238064\n",
+ "[869]\teval-rmse:0.26382\ttrain-rmse:0.238053\n",
+ "[870]\teval-rmse:0.263826\ttrain-rmse:0.238028\n",
+ "[871]\teval-rmse:0.263836\ttrain-rmse:0.238011\n",
+ "[872]\teval-rmse:0.263837\ttrain-rmse:0.237994\n",
+ "[873]\teval-rmse:0.263837\ttrain-rmse:0.237988\n",
+ "[874]\teval-rmse:0.263846\ttrain-rmse:0.237969\n",
+ "[875]\teval-rmse:0.263847\ttrain-rmse:0.237961\n",
+ "[876]\teval-rmse:0.263865\ttrain-rmse:0.237941\n",
+ "[877]\teval-rmse:0.263868\ttrain-rmse:0.237931\n",
+ "[878]\teval-rmse:0.263869\ttrain-rmse:0.237914\n",
+ "[879]\teval-rmse:0.263884\ttrain-rmse:0.237897\n",
+ "[880]\teval-rmse:0.263892\ttrain-rmse:0.237883\n",
+ "[881]\teval-rmse:0.263896\ttrain-rmse:0.237869\n",
+ "[882]\teval-rmse:0.263893\ttrain-rmse:0.237857\n",
+ "[883]\teval-rmse:0.263889\ttrain-rmse:0.237845\n",
+ "[884]\teval-rmse:0.263894\ttrain-rmse:0.237829\n",
+ "[885]\teval-rmse:0.263886\ttrain-rmse:0.237811\n",
+ "[886]\teval-rmse:0.263884\ttrain-rmse:0.237806\n",
+ "[887]\teval-rmse:0.263886\ttrain-rmse:0.237796\n",
+ "[888]\teval-rmse:0.263889\ttrain-rmse:0.237781\n",
+ "[889]\teval-rmse:0.263884\ttrain-rmse:0.23776\n",
+ "[890]\teval-rmse:0.263896\ttrain-rmse:0.237746\n",
+ "[891]\teval-rmse:0.263896\ttrain-rmse:0.237739\n",
+ "[892]\teval-rmse:0.263899\ttrain-rmse:0.237726\n",
+ "[893]\teval-rmse:0.263901\ttrain-rmse:0.237715\n",
+ "[894]\teval-rmse:0.263907\ttrain-rmse:0.2377\n",
+ "[895]\teval-rmse:0.263908\ttrain-rmse:0.237686\n",
+ "[896]\teval-rmse:0.263902\ttrain-rmse:0.237676\n",
+ "[897]\teval-rmse:0.263916\ttrain-rmse:0.237662\n",
+ "[898]\teval-rmse:0.263911\ttrain-rmse:0.237644\n",
+ "[899]\teval-rmse:0.263909\ttrain-rmse:0.237634\n",
+ "[900]\teval-rmse:0.26391\ttrain-rmse:0.23762\n",
+ "[901]\teval-rmse:0.263915\ttrain-rmse:0.237613\n",
+ "[902]\teval-rmse:0.263923\ttrain-rmse:0.237603\n",
+ "[903]\teval-rmse:0.263915\ttrain-rmse:0.237576\n",
+ "[904]\teval-rmse:0.263916\ttrain-rmse:0.237561\n",
+ "[905]\teval-rmse:0.263921\ttrain-rmse:0.237544\n",
+ "[906]\teval-rmse:0.263923\ttrain-rmse:0.237535\n",
+ "[907]\teval-rmse:0.263929\ttrain-rmse:0.237514\n",
+ "[908]\teval-rmse:0.263928\ttrain-rmse:0.237492\n",
+ "[909]\teval-rmse:0.263943\ttrain-rmse:0.23748\n",
+ "[910]\teval-rmse:0.263958\ttrain-rmse:0.237463\n",
+ "[911]\teval-rmse:0.263957\ttrain-rmse:0.237453\n",
+ "[912]\teval-rmse:0.263954\ttrain-rmse:0.237442\n",
+ "[913]\teval-rmse:0.263952\ttrain-rmse:0.237435\n",
+ "[914]\teval-rmse:0.263956\ttrain-rmse:0.237426\n",
+ "[915]\teval-rmse:0.263959\ttrain-rmse:0.237416\n",
+ "[916]\teval-rmse:0.263979\ttrain-rmse:0.237405\n",
+ "[917]\teval-rmse:0.263982\ttrain-rmse:0.237386\n",
+ "[918]\teval-rmse:0.263991\ttrain-rmse:0.237376\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[919]\teval-rmse:0.263995\ttrain-rmse:0.237365\n",
+ "[920]\teval-rmse:0.263994\ttrain-rmse:0.237359\n",
+ "[921]\teval-rmse:0.263996\ttrain-rmse:0.237353\n",
+ "[922]\teval-rmse:0.264001\ttrain-rmse:0.237347\n",
+ "[923]\teval-rmse:0.264007\ttrain-rmse:0.237341\n",
+ "[924]\teval-rmse:0.264029\ttrain-rmse:0.237323\n",
+ "[925]\teval-rmse:0.26403\ttrain-rmse:0.237318\n",
+ "[926]\teval-rmse:0.264031\ttrain-rmse:0.237309\n",
+ "[927]\teval-rmse:0.264038\ttrain-rmse:0.237291\n",
+ "[928]\teval-rmse:0.264042\ttrain-rmse:0.237283\n",
+ "[929]\teval-rmse:0.264037\ttrain-rmse:0.237265\n",
+ "[930]\teval-rmse:0.264035\ttrain-rmse:0.237258\n",
+ "[931]\teval-rmse:0.264037\ttrain-rmse:0.23725\n",
+ "[932]\teval-rmse:0.264034\ttrain-rmse:0.237232\n",
+ "[933]\teval-rmse:0.264042\ttrain-rmse:0.237219\n",
+ "[934]\teval-rmse:0.264043\ttrain-rmse:0.237213\n",
+ "[935]\teval-rmse:0.264045\ttrain-rmse:0.237205\n",
+ "[936]\teval-rmse:0.264047\ttrain-rmse:0.23718\n",
+ "[937]\teval-rmse:0.264049\ttrain-rmse:0.237169\n",
+ "[938]\teval-rmse:0.264047\ttrain-rmse:0.237149\n",
+ "[939]\teval-rmse:0.264052\ttrain-rmse:0.237139\n",
+ "[940]\teval-rmse:0.264052\ttrain-rmse:0.237119\n",
+ "[941]\teval-rmse:0.264055\ttrain-rmse:0.237104\n",
+ "[942]\teval-rmse:0.264066\ttrain-rmse:0.237082\n",
+ "[943]\teval-rmse:0.264056\ttrain-rmse:0.237076\n",
+ "[944]\teval-rmse:0.264052\ttrain-rmse:0.237066\n",
+ "[945]\teval-rmse:0.264061\ttrain-rmse:0.237054\n",
+ "[946]\teval-rmse:0.26406\ttrain-rmse:0.237047\n",
+ "[947]\teval-rmse:0.264065\ttrain-rmse:0.237043\n",
+ "[948]\teval-rmse:0.264062\ttrain-rmse:0.237037\n",
+ "[949]\teval-rmse:0.26406\ttrain-rmse:0.237019\n",
+ "[950]\teval-rmse:0.264065\ttrain-rmse:0.236998\n",
+ "[951]\teval-rmse:0.26407\ttrain-rmse:0.236986\n",
+ "[952]\teval-rmse:0.26408\ttrain-rmse:0.236965\n",
+ "[953]\teval-rmse:0.264088\ttrain-rmse:0.236949\n",
+ "[954]\teval-rmse:0.264086\ttrain-rmse:0.236942\n",
+ "[955]\teval-rmse:0.264086\ttrain-rmse:0.236926\n",
+ "[956]\teval-rmse:0.264085\ttrain-rmse:0.236919\n",
+ "[957]\teval-rmse:0.264084\ttrain-rmse:0.236905\n",
+ "[958]\teval-rmse:0.264084\ttrain-rmse:0.23689\n",
+ "[959]\teval-rmse:0.264086\ttrain-rmse:0.236881\n",
+ "[960]\teval-rmse:0.264084\ttrain-rmse:0.236867\n",
+ "[961]\teval-rmse:0.264077\ttrain-rmse:0.236856\n",
+ "[962]\teval-rmse:0.264079\ttrain-rmse:0.23685\n",
+ "[963]\teval-rmse:0.264079\ttrain-rmse:0.236845\n",
+ "[964]\teval-rmse:0.264081\ttrain-rmse:0.236832\n",
+ "[965]\teval-rmse:0.264092\ttrain-rmse:0.236813\n",
+ "[966]\teval-rmse:0.264096\ttrain-rmse:0.236801\n",
+ "[967]\teval-rmse:0.264101\ttrain-rmse:0.236788\n",
+ "[968]\teval-rmse:0.264105\ttrain-rmse:0.236783\n",
+ "[969]\teval-rmse:0.264107\ttrain-rmse:0.236779\n",
+ "[970]\teval-rmse:0.264115\ttrain-rmse:0.236762\n",
+ "[971]\teval-rmse:0.264117\ttrain-rmse:0.236754\n",
+ "[972]\teval-rmse:0.264115\ttrain-rmse:0.236746\n",
+ "[973]\teval-rmse:0.264118\ttrain-rmse:0.236729\n",
+ "[974]\teval-rmse:0.264118\ttrain-rmse:0.236709\n",
+ "[975]\teval-rmse:0.264124\ttrain-rmse:0.2367\n",
+ "[976]\teval-rmse:0.264142\ttrain-rmse:0.236677\n",
+ "[977]\teval-rmse:0.264143\ttrain-rmse:0.236668\n",
+ "[978]\teval-rmse:0.264144\ttrain-rmse:0.236661\n",
+ "[979]\teval-rmse:0.264148\ttrain-rmse:0.236653\n",
+ "[980]\teval-rmse:0.264149\ttrain-rmse:0.236636\n",
+ "[981]\teval-rmse:0.264164\ttrain-rmse:0.236615\n",
+ "[982]\teval-rmse:0.264172\ttrain-rmse:0.236595\n",
+ "[983]\teval-rmse:0.264175\ttrain-rmse:0.236584\n",
+ "[984]\teval-rmse:0.264193\ttrain-rmse:0.236563\n",
+ "[985]\teval-rmse:0.264204\ttrain-rmse:0.236547\n",
+ "[986]\teval-rmse:0.264201\ttrain-rmse:0.236529\n",
+ "[987]\teval-rmse:0.264221\ttrain-rmse:0.236513\n",
+ "[988]\teval-rmse:0.264227\ttrain-rmse:0.236499\n",
+ "[989]\teval-rmse:0.264221\ttrain-rmse:0.236489\n",
+ "[990]\teval-rmse:0.264222\ttrain-rmse:0.236479\n",
+ "[991]\teval-rmse:0.264221\ttrain-rmse:0.236466\n",
+ "[992]\teval-rmse:0.264218\ttrain-rmse:0.236454\n",
+ "[993]\teval-rmse:0.264207\ttrain-rmse:0.236437\n",
+ "[994]\teval-rmse:0.264209\ttrain-rmse:0.236433\n",
+ "[995]\teval-rmse:0.26421\ttrain-rmse:0.236422\n",
+ "[996]\teval-rmse:0.264214\ttrain-rmse:0.236414\n",
+ "[997]\teval-rmse:0.264217\ttrain-rmse:0.236409\n",
+ "[998]\teval-rmse:0.264225\ttrain-rmse:0.23639\n",
+ "[999]\teval-rmse:0.26424\ttrain-rmse:0.236364\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "<xgboost.core.Booster at 0x2aaaffb5b0f0>"
+ ]
+ },
+ "execution_count": 27,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Train model\n",
+ "xgb.train(param,dtrain,num_round,watchlist)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# this is where your model is being trained\n",
+ "\n",
+ "reg.fit(x_train,y_train)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# for linear models you can enable the following comment and check out all the coefficients of yout linear model\n",
+ "#reg.coef_"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# the 20% of the test data that are used for testing purpose\n",
+ "#a=reg.predict(x_test)\n",
+ "b=reg.predict(x_train)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# ensuring that the output has the correct dimensions\n",
+ "#a.shape = (a.size, 1)\n",
+ "b.shape = (b.size, 1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# calculate the mean square error (lower the error better yourmodel is)\n",
+ "#TestRMSE = np.sqrt(np.mean((a-y_test.values)**2))\n",
+ "#display('Test RMSE = {}'.format(TestRMSE))\n",
+ "\n",
+ "TrainRMSE = np.sqrt(np.mean((b-y_train.values)**2))\n",
+ "display('Train RMSE = {}'.format(TrainRMSE))\n",
+ "\n",
+ "#TestMAE = np.mean(np.abs(a-y_test.values))\n",
+ "#display('Test MAE = {}'.format(TestMAE))\n",
+ "\n",
+ "TrainMAE = np.mean(np.abs(b-y_train.values))\n",
+ "display('Train MAE = {}'.format(TrainMAE))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# R squared metric\n",
+ "display(\"Test R squared = {}\".format(r2_score(y_test,a)))\n",
+ "display(\"Train R squared = {}\".format(r2_score(y_train,b)))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# max_depth paramater tuning for the decision tree\n",
+ "max_depths = np.linspace(1, 32, 32, endpoint=True)\n",
+ "train_results = []\n",
+ "test_results = []\n",
+ "for max_depth in max_depths:\n",
+ " # Create the tree object\n",
+ " dt = tree.DecisionTreeRegressor(max_depth=max_depth)\n",
+ " \n",
+ " # Train the tree\n",
+ " dt.fit(x_train, y_train)\n",
+ " \n",
+ " # Predict the values for the training set\n",
+ " train_pred = dt.predict(x_train) \n",
+ " train_pred.shape = (train_pred.size,1)\n",
+ " \n",
+ " # Calculate RMSE and add to the train_results array\n",
+ " TrainRMSE = np.sqrt(np.mean((train_pred-y_train.values)**2))\n",
+ " train_results.append(TrainRMSE) \n",
+ " \n",
+ " # Predict the values for the test set\n",
+ " test_pred = dt.predict(x_test) \n",
+ " test_pred.shape = (test_pred.size,1)\n",
+ " \n",
+ " # Calculate RMSE and add to the train_results array\n",
+ " TestRMSE = np.sqrt(np.mean((test_pred-y_test.values)**2))\n",
+ " test_results.append(TestRMSE)\n",
+ "\n",
+ "from matplotlib.legend_handler import HandlerLine2D\n",
+ "line1, = plt.plot(max_depths, train_results, 'b', label = \"Train RMSE\")\n",
+ "line2, = plt.plot(max_depths, test_results, 'r', label = \"Test RMSE\")\n",
+ "\n",
+ "plt.legend(handler_map={line1: HandlerLine2D(numpoints=2)})\n",
+ "plt.ylabel('RMSE')\n",
+ "plt.xlabel('Tree depth')\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# min_samples_leaf paramater tuning for the decision tree\n",
+ "min_samples = np.linspace(5, 100, 20, endpoint=True)\n",
+ "train_results = []\n",
+ "test_results = []\n",
+ "for n in min_samples:\n",
+ " # Create the tree object\n",
+ " dt = tree.DecisionTreeRegressor(min_samples_leaf=n/x_train.size)\n",
+ " \n",
+ " # Train the tree\n",
+ " dt.fit(x_train, y_train)\n",
+ " \n",
+ " # Predict the values for the training set\n",
+ " train_pred = dt.predict(x_train) \n",
+ " train_pred.shape = (train_pred.size,1)\n",
+ " \n",
+ " # Calculate RMSE and add to the train_results array\n",
+ " TrainRMSE = np.sqrt(np.mean((train_pred-y_train.values)**2))\n",
+ " train_results.append(TrainRMSE) \n",
+ " \n",
+ " # Predict the values for the test set\n",
+ " test_pred = dt.predict(x_test) \n",
+ " test_pred.shape = (test_pred.size,1)\n",
+ " \n",
+ " # Calculate RMSE and add to the train_results array\n",
+ " TestRMSE = np.sqrt(np.mean((test_pred-y_test.values)**2))\n",
+ " test_results.append(TestRMSE)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from matplotlib.legend_handler import HandlerLine2D\n",
+ "line1, = plt.plot(min_samples, train_results, 'b', label = \"Train RMSE\")\n",
+ "line2, = plt.plot(min_samples, test_results, 'r', label = \"Test RMSE\")\n",
+ "\n",
+ "plt.legend(handler_map={line1: HandlerLine2D(numpoints=2)})\n",
+ "plt.ylabel('RMSE')\n",
+ "plt.xlabel('Min Samples per Leaf')\n",
+ "plt.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python [conda env:ctmodel-ml]",
+ "language": "python",
+ "name": "conda-env-ctmodel-ml-py"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.6"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}