diff --git a/.ipynb_checkpoints/README-checkpoint.md b/.ipynb_checkpoints/README-checkpoint.md
new file mode 100644
index 0000000..965b2a0
--- /dev/null
+++ b/.ipynb_checkpoints/README-checkpoint.md
@@ -0,0 +1,25 @@
+# Effective XGBoost by Matt Harrison - My Personal Take
+
+This repository contains my personal notes, examples, and code implementations based on the book "Effective XGBoost" by Matt Harrison. The purpose of this repo is to document my journey as I peer thru the mind of a master displaying his craft so I could glean some insights myself into building models that I could use for my projects.
+
+## Table of Contents
+
+2 Datasets 
+
+3 Exploratory Data Analysis 
+
+4 Tree Creation 
+
+5 Stumps on Real Data 
+ 
+6 Model Complexity & Hyperparameters 
+
+7 Tree Hyperparameters 
+
+8 Random Forest 
+
+9 XGBoost
+
+10 Early Stopping
+
+11 XGBoost Hyperparameters
\ No newline at end of file
diff --git a/.ipynb_checkpoints/chp11_XGBoostHyperparameters-checkpoint.ipynb b/.ipynb_checkpoints/chp11_XGBoostHyperparameters-checkpoint.ipynb
new file mode 100644
index 0000000..363fcab
--- /dev/null
+++ b/.ipynb_checkpoints/chp11_XGBoostHyperparameters-checkpoint.ipynb
@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/README.md b/README.md
index a045b44..965b2a0 100644
--- a/README.md
+++ b/README.md
@@ -6,25 +6,20 @@ This repository contains my personal notes, examples, and code implementations b
 
 2 Datasets 
 
-
 3 Exploratory Data Analysis 
 
-
 4 Tree Creation 
 
-
 5 Stumps on Real Data 
  
-
 6 Model Complexity & Hyperparameters 
 
-
 7 Tree Hyperparameters 
 
-
 8 Random Forest 
 
 9 XGBoost
 
 10 Early Stopping
 
+11 XGBoost Hyperparameters
\ No newline at end of file
diff --git a/chp10_EarlyStopping.ipynb b/chp10_EarlyStopping.ipynb
index c6f8c74..cf31b2d 100644
--- a/chp10_EarlyStopping.ipynb
+++ b/chp10_EarlyStopping.ipynb
@@ -169,7 +169,8 @@
       "[28]\tvalidation_0-logloss:0.38837\tvalidation_1-logloss:0.51135\n",
       "[29]\tvalidation_0-logloss:0.38569\tvalidation_1-logloss:0.51202\n",
       "[30]\tvalidation_0-logloss:0.37945\tvalidation_1-logloss:0.51352\n",
-      "[31]\tvalidation_0-logloss:0.37840\tvalidation_1-logloss:0.51545\n"
+      "[31]\tvalidation_0-logloss:0.37840\tvalidation_1-logloss:0.51545\n",
+      "[32]\tvalidation_0-logloss:0.37538\tvalidation_1-logloss:0.51581\n"
      ]
     },
     {
@@ -331,7 +332,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 6,
    "id": "88e90c50-2933-4822-9d5e-b18e9bfce7d7",
    "metadata": {},
    "outputs": [
@@ -404,7 +405,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 7,
    "id": "f22011c4-74af-4447-be73-0a1e2fe70a09",
    "metadata": {},
    "outputs": [
@@ -433,7 +434,7 @@
        "0.7558011049723757"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -458,7 +459,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 8,
    "id": "f4058e18-de3e-412c-8391-568c771bf77a",
    "metadata": {},
    "outputs": [
@@ -468,7 +469,7 @@
        "0.7458563535911602"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -500,7 +501,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 9,
    "id": "0d0042a9-f9ee-4982-899a-3e12e9cd4ad7",
    "metadata": {},
    "outputs": [
@@ -545,8 +546,7 @@
       "[34]\tvalidation_0-error:0.15261\tvalidation_1-error:0.25525\n",
       "[35]\tvalidation_0-error:0.15213\tvalidation_1-error:0.25525\n",
       "[36]\tvalidation_0-error:0.15166\tvalidation_1-error:0.25525\n",
-      "[37]\tvalidation_0-error:0.14550\tvalidation_1-error:0.25525\n",
-      "[38]\tvalidation_0-error:0.14597\tvalidation_1-error:0.25083\n"
+      "[37]\tvalidation_0-error:0.14550\tvalidation_1-error:0.25525\n"
      ]
     },
     {
@@ -555,7 +555,7 @@
        "0.7624309392265194"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -569,7 +569,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 10,
    "id": "e3887492-68a4-4711-8f0c-b2b9fc0dc5d0",
    "metadata": {},
    "outputs": [
@@ -579,7 +579,7 @@
        "19"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/chp11_XGBoostHyperparameters.ipynb b/chp11_XGBoostHyperparameters.ipynb
new file mode 100644
index 0000000..3340878
--- /dev/null
+++ b/chp11_XGBoostHyperparameters.ipynb
@@ -0,0 +1,720 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "2f83e84f-509e-4030-8c97-efa649a2b93d",
+   "metadata": {},
+   "source": [
+    "## 11.1 Hyperparameters\n",
+    "In programming, a parameter lets us control\n",
+    "how a function behaves. Hyperparameters allow us to control how a machine-learning model\n",
+    "behaves.\n",
+    "\n",
+    "Hyperparameters are values that control the behavior of the model and can be adjusted to improve its performance. Tuning hyperparameters involves finding the best values for them.\n",
+    "\n",
+    "XGBoost has a large range of hyperparameters that can be classified into four distinct categories: General Parameters, Booster Parameters, Learning Task Parameters, and Command Line Parameters. General parameters guide the overall functioning of the model and relate to the booster being used. Booster parameters depend on the choice of the booster. Learning task parameters decide on the learning scenario. For example, regression tasks may use different parameters with ranking tasks. Command line parameters relate to behavior of CLI version of XGBoost.\n",
+    "\n",
+    "### tree creation hyperparameters\n",
+    "* `'max_depth'` specifies the maximum depth of a tree and controls the complexity of the model. A larger value for max_depth allows for more feature interactions but increases the risk of overfitting. This one ranges from 0 to infinity.\n",
+    "* `'max_leaves'` specifies the maximum number of leaves in a tree and can be used to control model complexity. This one ranges from 0 to infinity.\n",
+    "* `'min_child_weight'` specifies the minimum sum of instance weight needed in a child and can be used to control overfitting by setting a larger value. This one ranges from 0 to infinity.\n",
+    "* `'grow_policy'` determines how new nodes are added to the tree and can be set to either “depthwise” or \"lossguide\"\n",
+    "* `'tree_method'` specifies the algorithm used for tree construction and can be set to “auto”, “exact”, “approx”, “hist”, or \"gpu_hist\".\n",
+    "\n",
+    "### sampling hyperparameters\n",
+    "* `'colsample_bytree'`, `'colsample_bylevel'`, and `'colsample_bynode'` control the subsampling of columns at each tree, level, and node split respectively. These hyperparameters can be used to control overfitting by setting a value less than 1.\n",
+    "* `'subsample '`controls the subsampling of rows before each boosting round and can also be used to control overfitting by setting a value less than 1.01. When subsample is not equal to 1.0, the model performs stochastic gradient descent.\n",
+    "\n",
+    "## 11.2 Examining Hyperparameters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "734c6b6c-709b-4a3d-a39e-544f102dc012",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import dtreeviz\n",
+    "from feature_engine import encoding, imputation\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "from sklearn import base, compose, datasets, ensemble, metrics, model_selection, pipeline, preprocessing, tree\n",
+    "import scikitplot\n",
+    "import xgboost as xgb\n",
+    "import yellowbrick.model_selection as ms\n",
+    "from yellowbrick import classifier\n",
+    "import urllib\n",
+    "import zipfile\n",
+    "\n",
+    "from EffectiveXGBoost import *"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "abf9fa95-dc9e-4bbc-995b-ea2061f6a186",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "G:\\My Drive\\SisengAI\\AlgorithmicTrading\\code_rebuilding\\MattHarrison\\EffectiveXGBoost\\EffectiveXGBoost_MyTake\\EffectiveXGBoost.py:56: DtypeWarning: Columns (0,2,8,10,21,23,24,25,26,27,28,44,56,64,83,85,87,107,109,123,125,150,157,172,174,194,210,218,219,223,246,249,262,264,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,304,306,325,326,329,341,368,371,384,385,389,390,391,393,394) have mixed types. Specify dtype option on import or set low_memory=False.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'objective': 'binary:logistic',\n",
+       " 'use_label_encoder': False,\n",
+       " 'base_score': 0.5,\n",
+       " 'booster': 'gbtree',\n",
+       " 'callbacks': None,\n",
+       " 'colsample_bylevel': 1,\n",
+       " 'colsample_bynode': 1,\n",
+       " 'colsample_bytree': 1,\n",
+       " 'early_stopping_rounds': None,\n",
+       " 'enable_categorical': False,\n",
+       " 'eval_metric': None,\n",
+       " 'gamma': 0,\n",
+       " 'gpu_id': -1,\n",
+       " 'grow_policy': 'depthwise',\n",
+       " 'importance_type': None,\n",
+       " 'interaction_constraints': '',\n",
+       " 'learning_rate': 0.300000012,\n",
+       " 'max_bin': 256,\n",
+       " 'max_cat_to_onehot': 4,\n",
+       " 'max_delta_step': 0,\n",
+       " 'max_depth': 6,\n",
+       " 'max_leaves': 0,\n",
+       " 'min_child_weight': 1,\n",
+       " 'missing': nan,\n",
+       " 'monotone_constraints': '()',\n",
+       " 'n_estimators': 100,\n",
+       " 'n_jobs': 0,\n",
+       " 'num_parallel_tree': 1,\n",
+       " 'predictor': 'auto',\n",
+       " 'random_state': 0,\n",
+       " 'reg_alpha': 0,\n",
+       " 'reg_lambda': 1,\n",
+       " 'sampling_method': 'uniform',\n",
+       " 'scale_pos_weight': 1,\n",
+       " 'subsample': 1,\n",
+       " 'tree_method': 'exact',\n",
+       " 'validate_parameters': 1,\n",
+       " 'verbosity': None}"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "path_url = 'https://github.com/mattharrison/datasets/raw/master/data/kaggle-survey-2018.zip'\n",
+    "file_name = 'kaggle-survey-2018.zip'\n",
+    "dataset = 'multipleChoiceResponses.csv'\n",
+    "\n",
+    "raw = extract_dataset(path_url, file_name, dataset)\n",
+    "\n",
+    "# Create raw X and raw y\n",
+    "kag_X, kag_y = prepX_y(raw, 'Q6')\n",
+    "\n",
+    "# Split data\n",
+    "kag_X_train, kag_X_test, kag_y_train, kag_y_test = (model_selection\n",
+    "                                                    .train_test_split(kag_X, \n",
+    "                                                                      kag_y, \n",
+    "                                                                      test_size=.3, \n",
+    "                                                                      random_state=42, \n",
+    "                                                                      stratify=kag_y)\n",
+    "                                                   )\n",
+    "\n",
+    "\n",
+    "# Transform X with pipeline\n",
+    "pline = pipeline.Pipeline(\n",
+    "    [('tweak', PrepDataTransformer()),\n",
+    "    ('cat', encoding.OneHotEncoder(top_categories=5, drop_last=True,\n",
+    "    variables=['Q1', 'Q3', 'major'])),\n",
+    "    ('num_impute', imputation.MeanMedianImputer(imputation_method='median',\n",
+    "                variables=['education', 'years_exp']))]\n",
+    "    )\n",
+    "\n",
+    "X_train = pline.fit_transform(kag_X_train)\n",
+    "X_test = pline.transform(kag_X_test)\n",
+    "\n",
+    "# Transform y with label encoder\n",
+    "label_encoder = preprocessing.LabelEncoder()\n",
+    "label_encoder.fit(kag_y_train)\n",
+    "y_train = label_encoder.transform(kag_y_train)\n",
+    "y_test = label_encoder.transform(kag_y_test)\n",
+    "\n",
+    "# Combined Data for cross validation/etc\n",
+    "X = pd.concat([X_train, X_test], axis='index')\n",
+    "y = pd.Series([*y_train, *y_test], index=X.index)\n",
+    "\n",
+    "# Default training\n",
+    "xg = xgb.XGBClassifier()\n",
+    "xg.fit(X_train, y_train)\n",
+    "xg.get_params()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b156cd62-8ba9-494d-a093-ec261b66a263",
+   "metadata": {},
+   "source": [
+    "Validation curves are plots that show how the performance of the model changes as the value of a specific hyperparameter is changed. By looking at these plots, you can see which values of the hyperparameter yield the best results.\n",
+    "\n",
+    "We will use our old friend `validation_curve` function from the `Yellowbrick` library to plot a validation curve for the `'gamma'` hyperparameter. _Gamma_ is a hyperparameter that controls how much a tree can grow. It limits growth unless a specified loss reduction is met. The larger the value of gamma, the more conservative or simple the model will be."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "79344be9-dd6e-4ee6-bbf2-426d54ff9e4c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 864x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-3 {color: black;background-color: white;}#sk-container-id-3 pre{padding: 0;}#sk-container-id-3 div.sk-toggleable {background-color: white;}#sk-container-id-3 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-3 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-3 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-3 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-3 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-3 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-3 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-3 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-3 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-3 div.sk-item {position: relative;z-index: 1;}#sk-container-id-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-3 div.sk-item::before, #sk-container-id-3 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-3 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-3 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-3 div.sk-label-container {text-align: center;}#sk-container-id-3 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ValidationCurve(ax=&lt;AxesSubplot:title={&#x27;center&#x27;:&#x27;Validation Curve for XGBClassifier&#x27;}, xlabel=&#x27;gamma&#x27;, ylabel=&#x27;score&#x27;&gt;,\n",
+       "                estimator=XGBClassifier(base_score=None, booster=None,\n",
+       "                                        callbacks=None, colsample_bylevel=None,\n",
+       "                                        colsample_bynode=None,\n",
+       "                                        colsample_bytree=None,\n",
+       "                                        early_stopping_rounds=None,\n",
+       "                                        enable_categorical=False,\n",
+       "                                        eval_metric=None, gamma=None,\n",
+       "                                        gpu_id=None, grow_poli...\n",
+       "                                        learning_rate=None, max_bin=None,\n",
+       "                                        max_cat_to_onehot=None,\n",
+       "                                        max_delta_step=None, max_depth=None,\n",
+       "                                        max_leaves=None, min_child_weight=None,\n",
+       "                                        missing=nan, monotone_constraints=None,\n",
+       "                                        n_estimators=100, n_jobs=None,\n",
+       "                                        num_parallel_tree=None, predictor=None,\n",
+       "                                        random_state=None, reg_alpha=None,\n",
+       "                                        reg_lambda=None, ...),\n",
+       "                n_jobs=-1, param_name=&#x27;gamma&#x27;,\n",
+       "                param_range=array([ 0. ,  0.5,  1. ,  5. , 10. , 20. , 30. ]))</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">ValidationCurve</label><div class=\"sk-toggleable__content\"><pre>ValidationCurve(ax=&lt;AxesSubplot:title={&#x27;center&#x27;:&#x27;Validation Curve for XGBClassifier&#x27;}, xlabel=&#x27;gamma&#x27;, ylabel=&#x27;score&#x27;&gt;,\n",
+       "                estimator=XGBClassifier(base_score=None, booster=None,\n",
+       "                                        callbacks=None, colsample_bylevel=None,\n",
+       "                                        colsample_bynode=None,\n",
+       "                                        colsample_bytree=None,\n",
+       "                                        early_stopping_rounds=None,\n",
+       "                                        enable_categorical=False,\n",
+       "                                        eval_metric=None, gamma=None,\n",
+       "                                        gpu_id=None, grow_poli...\n",
+       "                                        learning_rate=None, max_bin=None,\n",
+       "                                        max_cat_to_onehot=None,\n",
+       "                                        max_delta_step=None, max_depth=None,\n",
+       "                                        max_leaves=None, min_child_weight=None,\n",
+       "                                        missing=nan, monotone_constraints=None,\n",
+       "                                        n_estimators=100, n_jobs=None,\n",
+       "                                        num_parallel_tree=None, predictor=None,\n",
+       "                                        random_state=None, reg_alpha=None,\n",
+       "                                        reg_lambda=None, ...),\n",
+       "                n_jobs=-1, param_name=&#x27;gamma&#x27;,\n",
+       "                param_range=array([ 0. ,  0.5,  1. ,  5. , 10. , 20. , 30. ]))</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: XGBClassifier</label><div class=\"sk-toggleable__content\"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
+       "              colsample_bylevel=None, colsample_bynode=None,\n",
+       "              colsample_bytree=None, early_stopping_rounds=None,\n",
+       "              enable_categorical=False, eval_metric=None, gamma=None,\n",
+       "              gpu_id=None, grow_policy=None, importance_type=None,\n",
+       "              interaction_constraints=None, learning_rate=None, max_bin=None,\n",
+       "              max_cat_to_onehot=None, max_delta_step=None, max_depth=None,\n",
+       "              max_leaves=None, min_child_weight=None, missing=nan,\n",
+       "              monotone_constraints=None, n_estimators=100, n_jobs=None,\n",
+       "              num_parallel_tree=None, predictor=None, random_state=None,\n",
+       "              reg_alpha=None, reg_lambda=None, ...)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBClassifier</label><div class=\"sk-toggleable__content\"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
+       "              colsample_bylevel=None, colsample_bynode=None,\n",
+       "              colsample_bytree=None, early_stopping_rounds=None,\n",
+       "              enable_categorical=False, eval_metric=None, gamma=None,\n",
+       "              gpu_id=None, grow_policy=None, importance_type=None,\n",
+       "              interaction_constraints=None, learning_rate=None, max_bin=None,\n",
+       "              max_cat_to_onehot=None, max_delta_step=None, max_depth=None,\n",
+       "              max_leaves=None, min_child_weight=None, missing=nan,\n",
+       "              monotone_constraints=None, n_estimators=100, n_jobs=None,\n",
+       "              num_parallel_tree=None, predictor=None, random_state=None,\n",
+       "              reg_alpha=None, reg_lambda=None, ...)</pre></div></div></div></div></div></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "ValidationCurve(ax=<AxesSubplot:title={'center':'Validation Curve for XGBClassifier'}, xlabel='gamma', ylabel='score'>,\n",
+       "                estimator=XGBClassifier(base_score=None, booster=None,\n",
+       "                                        callbacks=None, colsample_bylevel=None,\n",
+       "                                        colsample_bynode=None,\n",
+       "                                        colsample_bytree=None,\n",
+       "                                        early_stopping_rounds=None,\n",
+       "                                        enable_categorical=False,\n",
+       "                                        eval_metric=None, gamma=None,\n",
+       "                                        gpu_id=None, grow_poli...\n",
+       "                                        learning_rate=None, max_bin=None,\n",
+       "                                        max_cat_to_onehot=None,\n",
+       "                                        max_delta_step=None, max_depth=None,\n",
+       "                                        max_leaves=None, min_child_weight=None,\n",
+       "                                        missing=nan, monotone_constraints=None,\n",
+       "                                        n_estimators=100, n_jobs=None,\n",
+       "                                        num_parallel_tree=None, predictor=None,\n",
+       "                                        random_state=None, reg_alpha=None,\n",
+       "                                        reg_lambda=None, ...),\n",
+       "                n_jobs=-1, param_name='gamma',\n",
+       "                param_range=array([ 0. ,  0.5,  1. ,  5. , 10. , 20. , 30. ]))"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(12, 7))\n",
+    "ms.validation_curve(xgb.XGBClassifier(), X_train, y_train, param_name='gamma', param_range=[0, .5, 1,5,10, 20, 30], n_jobs=-1, ax=ax)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "30b95596-e376-46a0-a26c-81bcfacffc54",
+   "metadata": {},
+   "source": [
+    "From the validation curve, spots between 10 and 20 all look good.\n",
+    "\n",
+    "## 11.4 Intuitive Understanding of Learning Rate\n",
+    "\n",
+    "You need to find the right balance for the learning_rate hyperparameter.\n",
+    "\n",
+    "If you set the learning_rate too high, your model will be over-confident and over-fit the data. This means that it will memorize the training data instead of learning from it, and will not perform well on new data. On the other hand, if you set the learning_rate too low, your model will take too long to learn and may never reach its full potential.\n",
+    "\n",
+    "Finding the right value for the learning_rate hyperparameter involves experimentation. You need to try different values and see which one gives you the best performance. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "0dd5025b-9880-47cc-97e8-890b1238724e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-4 {color: black;background-color: white;}#sk-container-id-4 pre{padding: 0;}#sk-container-id-4 div.sk-toggleable {background-color: white;}#sk-container-id-4 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-4 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-4 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-4 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-4 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-4 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-4 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-4 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-4 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-4 div.sk-item {position: relative;z-index: 1;}#sk-container-id-4 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-4 div.sk-item::before, #sk-container-id-4 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-4 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-4 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-4 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-4 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-4 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-4 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-4 div.sk-label-container {text-align: center;}#sk-container-id-4 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-4 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>XGBClassifier(base_score=0.5, booster=&#x27;gbtree&#x27;, callbacks=None,\n",
+       "              colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n",
+       "              early_stopping_rounds=None, enable_categorical=False,\n",
+       "              eval_metric=None, gamma=0, gpu_id=-1, grow_policy=&#x27;depthwise&#x27;,\n",
+       "              importance_type=None, interaction_constraints=&#x27;&#x27;, learning_rate=1,\n",
+       "              max_bin=256, max_cat_to_onehot=4, max_delta_step=0, max_depth=2,\n",
+       "              max_leaves=0, min_child_weight=1, missing=nan,\n",
+       "              monotone_constraints=&#x27;()&#x27;, n_estimators=100, n_jobs=0,\n",
+       "              num_parallel_tree=1, predictor=&#x27;auto&#x27;, random_state=0,\n",
+       "              reg_alpha=0, reg_lambda=1, ...)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" checked><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBClassifier</label><div class=\"sk-toggleable__content\"><pre>XGBClassifier(base_score=0.5, booster=&#x27;gbtree&#x27;, callbacks=None,\n",
+       "              colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n",
+       "              early_stopping_rounds=None, enable_categorical=False,\n",
+       "              eval_metric=None, gamma=0, gpu_id=-1, grow_policy=&#x27;depthwise&#x27;,\n",
+       "              importance_type=None, interaction_constraints=&#x27;&#x27;, learning_rate=1,\n",
+       "              max_bin=256, max_cat_to_onehot=4, max_delta_step=0, max_depth=2,\n",
+       "              max_leaves=0, min_child_weight=1, missing=nan,\n",
+       "              monotone_constraints=&#x27;()&#x27;, n_estimators=100, n_jobs=0,\n",
+       "              num_parallel_tree=1, predictor=&#x27;auto&#x27;, random_state=0,\n",
+       "              reg_alpha=0, reg_lambda=1, ...)</pre></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "XGBClassifier(base_score=0.5, booster='gbtree', callbacks=None,\n",
+       "              colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n",
+       "              early_stopping_rounds=None, enable_categorical=False,\n",
+       "              eval_metric=None, gamma=0, gpu_id=-1, grow_policy='depthwise',\n",
+       "              importance_type=None, interaction_constraints='', learning_rate=1,\n",
+       "              max_bin=256, max_cat_to_onehot=4, max_delta_step=0, max_depth=2,\n",
+       "              max_leaves=0, min_child_weight=1, missing=nan,\n",
+       "              monotone_constraints='()', n_estimators=100, n_jobs=0,\n",
+       "              num_parallel_tree=1, predictor='auto', random_state=0,\n",
+       "              reg_alpha=0, reg_lambda=1, ...)"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# check impact of learning weight on scores\n",
+    "xg_lr1 = xgb.XGBClassifier(learning_rate=1, max_depth=2)\n",
+    "xg_lr1.fit(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "1d008a59-4dbc-432e-aedc-ac9f2695375c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 3600x7200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(6,12), dpi=600)\n",
+    "_=xgb.plot_tree(xg_lr1, num_trees=0, ax=ax)\n",
+    "\n",
+    "my_dot_export(xg_lr1, n_trees=0, filename='img/xg_depth2_tree0.dot',\n",
+    "title='Learning Rate set to 1')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "17ab4d87-bd33-4143-b7d2-0fd5fe3599a2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 3600x7200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# check impact of learning weight on scores\n",
+    "xg_lr001 = xgb.XGBClassifier(learning_rate=.001, max_depth=2)\n",
+    "xg_lr001.fit(X_train, y_train)\n",
+    "\n",
+    "fig, ax = plt.subplots(figsize=(6,12), dpi=600)\n",
+    "_=xgb.plot_tree(xg_lr001, num_trees=0, ax=ax)\n",
+    "\n",
+    "my_dot_export(xg_lr001, n_trees=0, filename='img/xg_depth2_tree0_lr001.dot',\n",
+    "title='Learning Rate set to .001')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b8d8e6f5-9856-42ea-bb69-937fc9c1d436",
+   "metadata": {},
+   "source": [
+    "## 11.5 Grid Search\n",
+    "\n",
+    "Since there are many hyperparameters and some of them interact with each other, it can be difficult to know which combination of values will give the best performance.\n",
+    "\n",
+    "One way to find the best combination of hyperparameters is to use a grid search. This involves trying all possible combinations of hyperparameter values and seeing which one gives the best performance. The `GridSearchCV` class from the scikit-learn library can help with this. You provide it with a mapping of hyperparameters to potential values for each hyperparameter, and it will loop through all combinations and keep track of the best ones.\n",
+    "\n",
+    "However, grid search can be computationally expensive and time-consuming, especially when there are many hyperparameters to test and many possible values for each one. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "6fa2a1ae-730a-44ee-9cec-f0a04b698d47",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0]\tvalidation_0-logloss:0.64544\n",
+      "[33]\tvalidation_0-logloss:0.50970\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'learning_rate': 0.3,\n",
+       " 'max_depth': 2,\n",
+       " 'n_estimators': 200,\n",
+       " 'n_jobs': -1,\n",
+       " 'random_state': 42,\n",
+       " 'reg_lambda': 0,\n",
+       " 'subsample': 1}"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn import model_selection\n",
+    "params = {'reg_lambda': [0], # No effect\n",
+    "        'learning_rate': [.1, .3], # makes each boost more conservative\n",
+    "        'subsample': [.7, 1],\n",
+    "        'max_depth': [2, 3],\n",
+    "        'random_state': [42],\n",
+    "        'n_jobs': [-1],\n",
+    "        'n_estimators': [200]}\n",
+    "xgb2 = xgb.XGBClassifier(early_stopping_rounds=5)\n",
+    "cv = (model_selection.GridSearchCV(xgb2, params, cv=3, n_jobs=-1)\n",
+    "      .fit(X_train, y_train, eval_set=[(X_test, y_test)], verbose=50))\n",
+    "\n",
+    "# a dictionary of the hyperparameters with the best result\n",
+    "cv.best_params_"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "4eec350e-6335-4ecc-b19c-899af7aee33c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0]\tvalidation_0-logloss:0.64709\tvalidation_1-logloss:0.64544\n",
+      "[10]\tvalidation_0-logloss:0.54430\tvalidation_1-logloss:0.53771\n",
+      "[20]\tvalidation_0-logloss:0.52311\tvalidation_1-logloss:0.51780\n",
+      "[30]\tvalidation_0-logloss:0.51253\tvalidation_1-logloss:0.51011\n",
+      "[40]\tvalidation_0-logloss:0.50731\tvalidation_1-logloss:0.50763\n",
+      "[50]\tvalidation_0-logloss:0.50150\tvalidation_1-logloss:0.50626\n",
+      "[60]\tvalidation_0-logloss:0.49832\tvalidation_1-logloss:0.50483\n",
+      "[70]\tvalidation_0-logloss:0.49528\tvalidation_1-logloss:0.50508\n",
+      "[80]\tvalidation_0-logloss:0.49255\tvalidation_1-logloss:0.50703\n",
+      "[90]\tvalidation_0-logloss:0.48966\tvalidation_1-logloss:0.50807\n",
+      "[100]\tvalidation_0-logloss:0.48718\tvalidation_1-logloss:0.50778\n",
+      "[110]\tvalidation_0-logloss:0.48625\tvalidation_1-logloss:0.50810\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-5 {color: black;background-color: white;}#sk-container-id-5 pre{padding: 0;}#sk-container-id-5 div.sk-toggleable {background-color: white;}#sk-container-id-5 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-5 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-5 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-5 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-5 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-5 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-5 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-5 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-5 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-5 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-5 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-5 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-5 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-5 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-5 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-5 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-5 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-5 div.sk-item {position: relative;z-index: 1;}#sk-container-id-5 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-5 div.sk-item::before, #sk-container-id-5 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-5 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-5 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-5 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-5 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-5 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-5 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-5 div.sk-label-container {text-align: center;}#sk-container-id-5 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-5 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-5\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>XGBClassifier(base_score=0.5, booster=&#x27;gbtree&#x27;, callbacks=None,\n",
+       "              colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n",
+       "              early_stopping_rounds=50, enable_categorical=False,\n",
+       "              eval_metric=None, gamma=0, gpu_id=-1, grow_policy=&#x27;depthwise&#x27;,\n",
+       "              importance_type=None, interaction_constraints=&#x27;&#x27;,\n",
+       "              learning_rate=0.3, max_bin=256, max_cat_to_onehot=4,\n",
+       "              max_delta_step=0, max_depth=2, max_leaves=0, min_child_weight=1,\n",
+       "              missing=nan, monotone_constraints=&#x27;()&#x27;, n_estimators=200,\n",
+       "              n_jobs=-1, num_parallel_tree=1, predictor=&#x27;auto&#x27;, random_state=42,\n",
+       "              reg_alpha=0, reg_lambda=0, ...)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-11\" type=\"checkbox\" checked><label for=\"sk-estimator-id-11\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBClassifier</label><div class=\"sk-toggleable__content\"><pre>XGBClassifier(base_score=0.5, booster=&#x27;gbtree&#x27;, callbacks=None,\n",
+       "              colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n",
+       "              early_stopping_rounds=50, enable_categorical=False,\n",
+       "              eval_metric=None, gamma=0, gpu_id=-1, grow_policy=&#x27;depthwise&#x27;,\n",
+       "              importance_type=None, interaction_constraints=&#x27;&#x27;,\n",
+       "              learning_rate=0.3, max_bin=256, max_cat_to_onehot=4,\n",
+       "              max_delta_step=0, max_depth=2, max_leaves=0, min_child_weight=1,\n",
+       "              missing=nan, monotone_constraints=&#x27;()&#x27;, n_estimators=200,\n",
+       "              n_jobs=-1, num_parallel_tree=1, predictor=&#x27;auto&#x27;, random_state=42,\n",
+       "              reg_alpha=0, reg_lambda=0, ...)</pre></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "XGBClassifier(base_score=0.5, booster='gbtree', callbacks=None,\n",
+       "              colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n",
+       "              early_stopping_rounds=50, enable_categorical=False,\n",
+       "              eval_metric=None, gamma=0, gpu_id=-1, grow_policy='depthwise',\n",
+       "              importance_type=None, interaction_constraints='',\n",
+       "              learning_rate=0.3, max_bin=256, max_cat_to_onehot=4,\n",
+       "              max_delta_step=0, max_depth=2, max_leaves=0, min_child_weight=1,\n",
+       "              missing=nan, monotone_constraints='()', n_estimators=200,\n",
+       "              n_jobs=-1, num_parallel_tree=1, predictor='auto', random_state=42,\n",
+       "              reg_alpha=0, reg_lambda=0, ...)"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "params = {'learning_rate': 0.3,\n",
+    "'max_depth': 2,\n",
+    "'n_estimators': 200,\n",
+    "'n_jobs': -1,\n",
+    "'random_state': 42,\n",
+    "'reg_lambda': 0,\n",
+    "'subsample': 1\n",
+    "}\n",
+    "xgb_grid = xgb.XGBClassifier(**params, early_stopping_rounds=50)\n",
+    "xgb_grid.fit(X_train, y_train, eval_set=[(X_train, y_train),(X_test, y_test)],verbose=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "fc9459b0-fc2f-42cb-b046-1e3b25483cea",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0]\tvalidation_0-logloss:0.61534\tvalidation_1-logloss:0.61775\n",
+      "[10]\tvalidation_0-logloss:0.45062\tvalidation_1-logloss:0.50430\n",
+      "[20]\tvalidation_0-logloss:0.40872\tvalidation_1-logloss:0.50839\n",
+      "[30]\tvalidation_0-logloss:0.37945\tvalidation_1-logloss:0.51352\n",
+      "[40]\tvalidation_0-logloss:0.35009\tvalidation_1-logloss:0.52234\n",
+      "[50]\tvalidation_0-logloss:0.33692\tvalidation_1-logloss:0.52726\n",
+      "[60]\tvalidation_0-logloss:0.32142\tvalidation_1-logloss:0.53397\n",
+      "[61]\tvalidation_0-logloss:0.32072\tvalidation_1-logloss:0.53429\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(0.7558011049723757, 0.7524861878453039)"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# vs default\n",
+    "xgb_def = xgb.XGBClassifier(early_stopping_rounds=50)\n",
+    "xgb_def.fit(X_train, y_train, eval_set=[(X_train, y_train), (X_test, y_test)], verbose=10)\n",
+    "\n",
+    "xgb_def.score(X_test, y_test), xgb_grid.score(X_test, y_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0a8a1cc7-07ab-4539-9b53-46c272e93215",
+   "metadata": {},
+   "source": [
+    "The default model performed slightly better than the model obtained through grid search. This can happen because the grid search used 3-fold cross-validation to find the best hyperparameters, but the final score was calculated against a single holdout set.\n",
+    "\n",
+    "K-fold cross-validation is a technique used to evaluate the performance of a model. It involves splitting the data into k folds or groups. Then, for each fold, the model is trained on all the other folds and tested on the reserved fold. This process is repeated for each fold and the results are averaged to get a more accurate estimate of the model’s performance.\n",
+    "\n",
+    "To run k-fold cross-validation outside of grid search, you can use the cross_val_score function from the scikit-learn library."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "12ce3576-980f-476b-b017-f353d6b35592",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.71352785, 0.72413793, 0.69496021, 0.74501992])"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results_default = model_selection.cross_val_score(xgb.XGBClassifier(), X=X, y=y, cv=4)\n",
+    "results_default"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "d09e7497-f960-4f94-9077-65d6566e6ee2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.7194114787534214"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results_default.mean()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ab79a4de-dd1d-4772-9bd7-3e4171615dec",
+   "metadata": {},
+   "source": [
+    "Let’s call cross_val_score again with a model created from our grid search hyperparameters."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "6383bc77-8637-4a92-b70e-32c35bd41326",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0.74137931 0.74137931 0.74801061 0.73572377]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0.7416232505873941"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results_grid = model_selection.cross_val_score(xgb.XGBClassifier(**params), X=X, y=y,cv=4)\n",
+    "print(results_grid)\n",
+    "results_grid.mean()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ecb7799c-bae4-4afa-9d48-36e3a209c045",
+   "metadata": {},
+   "source": [
+    "Our grid search model here seems to perform better for these folds of the data; and the\n",
+    "scores across the folds look more consistent. Probably the case that the test set we held\n",
+    "out for `X_test` is easier for the default model to predict."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04cb827e-e95d-4c84-af36-1a223cdaedbe",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.9.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/img/xg_depth2_tree0.dot b/img/xg_depth2_tree0.dot
new file mode 100644
index 0000000..f2dae18
--- /dev/null
+++ b/img/xg_depth2_tree0.dot
@@ -0,0 +1,28 @@
+digraph {
+    graph [ rankdir=TB ];
+  node [fontname = "Roboto Condensed"];
+    edge [fontname = "Roboto Thin"];
+    label = "Learning Rate set to 1"
+    fontname = "Roboto Condensed"
+    
+
+    0 [ label="r<0.5" ]
+    0 -> 1 [label="yes, missing" color="#0000FF"]
+    0 -> 2 [label="no" color="#FF0000"]
+
+    1 [ label="major_cs<0.5" ]
+    1 -> 3 [label="yes, missing" color="#0000FF"]
+    1 -> 4 [label="no" color="#FF0000"]
+
+    3 [ label="leaf=-0.282548487" ]
+
+    4 [ label="leaf=0.727272749" ]
+
+    2 [ label="major_cs<0.5" ]
+    2 -> 5 [label="yes, missing" color="#0000FF"]
+    2 -> 6 [label="no" color="#FF0000"]
+
+    5 [ label="leaf=-1.50783002" ]
+
+    6 [ label="leaf=-0.395721912" ]
+}
diff --git a/img/xg_depth2_tree0.png b/img/xg_depth2_tree0.png
new file mode 100644
index 0000000..f43ba59
Binary files /dev/null and b/img/xg_depth2_tree0.png differ
diff --git a/img/xg_depth2_tree0_lr001.dot b/img/xg_depth2_tree0_lr001.dot
new file mode 100644
index 0000000..cb01d4e
--- /dev/null
+++ b/img/xg_depth2_tree0_lr001.dot
@@ -0,0 +1,28 @@
+digraph {
+    graph [ rankdir=TB ];
+  node [fontname = "Roboto Condensed"];
+    edge [fontname = "Roboto Thin"];
+    label = "Learning Rate set to .001"
+    fontname = "Roboto Condensed"
+    
+
+    0 [ label="r<0.5" ]
+    0 -> 1 [label="yes, missing" color="#0000FF"]
+    0 -> 2 [label="no" color="#FF0000"]
+
+    1 [ label="major_cs<0.5" ]
+    1 -> 3 [label="yes, missing" color="#0000FF"]
+    1 -> 4 [label="no" color="#FF0000"]
+
+    3 [ label="leaf=-0.000282548513" ]
+
+    4 [ label="leaf=0.000727272767" ]
+
+    2 [ label="major_cs<0.5" ]
+    2 -> 5 [label="yes, missing" color="#0000FF"]
+    2 -> 6 [label="no" color="#FF0000"]
+
+    5 [ label="leaf=-0.00150783011" ]
+
+    6 [ label="leaf=-0.000395721931" ]
+}
diff --git a/img/xg_depth2_tree0_lr001.png b/img/xg_depth2_tree0_lr001.png
new file mode 100644
index 0000000..66cbd58
Binary files /dev/null and b/img/xg_depth2_tree0_lr001.png differ