Prac_SK4_Solutions.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Practice Exercise: Scikit-Learn 4\n",
    "### Cross-Validation and Hyper-parameter Tuning¶"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Objectives\n",
    "\n",
    "As in the [SK4 Tutorial](https://www.featureranking.com/tutorials/machine-learning-tutorials/sk-part-4-cross-validation-and-hyperparameter-tuning/), the objective of this practice notebook is to illustrate how you can perform cross-validation and hyper-parameter tuning using `Scikit-Learn`. You will also perform paired t-tests to determine statistically significant performance results, as explained [here](https://www.featureranking.com/tutorials/machine-learning-tutorials/sk-part-5-advanced-topics-pipelines-statistical-model-comparison-and-model-deployment/#4). \n",
    "\n",
    "You will be using the cleaned \"income data\" dataset. In the previous practices, you cleaned and transformed the raw `income data` and renamed the `income` column as `target` (with high income being the positive class). Including `target`, the cleaned data consists of 42 columns and 45,222 rows. Each column is numeric and between 0 and 1.\n",
    "\n",
    "In `GridSearchCV()`, try setting `n_jobs` to -2 for shorter run times with parallel processing. Here, -2 means use all core except 1. See [SK5 Tutorial](https://www.featureranking.com/tutorials/machine-learning-tutorials/sk-part-5-advanced-topics-pipelines-statistical-model-comparison-and-model-deployment/) for more details."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Instructions\n",
    "\n",
    "- For ease of computation, you will first randomly sample 5,000 rows from this dataset. \n",
    "- You will then split this sample into 70% train and 30% test datasets. \n",
    "- You will use the first set for **training**: you will fine tune your models using this train data. \n",
    "- You will use the second set for **testing**: you will perform cross-validation in a paired fashion using the test data and then you will compare the performance of your tuned models using a paired t-test.\n",
    "- You will use **stratified 5-fold cross-validation with no repetitions** during both training and testing.\n",
    "- For scoring, you will use AUC, that is, \"area under the ROC curve\". "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Some Bookkeeping\n",
    "\n",
    "- Define a variable called `num_samples` and set it to 5000. You will use this variable when sampling a smaller subset of the full set of instances.\n",
    "- Define a variable called `num_features` and set it to 10. Prior to fitting any models, you will perform feature selection by making use of this `num_features` variable.\n",
    "- Define a variable called `scoring_metric` and set it to to `'roc_auc'`. You will set `scoring` option in all `cross_val_score()` functions to this `scoring_metric` variable.\n",
    "\n",
    "You can achieve these by running the code chunk below:\n",
    "```Python\n",
    "import numpy as np\n",
    "np.random.seed(999)\n",
    "num_samples = 5000\n",
    "scoring_metric = 'roc_auc'\n",
    "num_features = 10\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise 0: Modeling Preparation\n",
    "\n",
    "- Read in the clean data `us_census_income_data_clean_encoded.csv` on GitHub [here](https://github.com/akmand/datasets). \n",
    "- Randomly sample 5000 rows using a random seed of 999.\n",
    "- Split the sampled data as 70% training set and the remaining 30% test set using a random seed of 999. \n",
    "- Remember to separate `target` during the splitting process. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "np.random.seed(999)\n",
    "num_samples = 5000\n",
    "scoring_metric = 'roc_auc'\n",
    "num_features = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(45222, 42)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>education_num</th>\n",
       "      <th>race</th>\n",
       "      <th>gender</th>\n",
       "      <th>hours_per_week</th>\n",
       "      <th>native_country</th>\n",
       "      <th>capital</th>\n",
       "      <th>workclass_federal_gov</th>\n",
       "      <th>workclass_local_gov</th>\n",
       "      <th>workclass_private</th>\n",
       "      <th>workclass_self_emp_inc</th>\n",
       "      <th>workclass_self_emp_not_inc</th>\n",
       "      <th>workclass_state_gov</th>\n",
       "      <th>workclass_without_pay</th>\n",
       "      <th>marital_status_divorced</th>\n",
       "      <th>marital_status_married_af_spouse</th>\n",
       "      <th>marital_status_married_civ_spouse</th>\n",
       "      <th>marital_status_married_spouse_absent</th>\n",
       "      <th>marital_status_never_married</th>\n",
       "      <th>marital_status_separated</th>\n",
       "      <th>marital_status_widowed</th>\n",
       "      <th>occupation_adm_clerical</th>\n",
       "      <th>occupation_armed_forces</th>\n",
       "      <th>occupation_craft_repair</th>\n",
       "      <th>occupation_exec_managerial</th>\n",
       "      <th>occupation_farming_fishing</th>\n",
       "      <th>occupation_handlers_cleaners</th>\n",
       "      <th>occupation_machine_op_inspct</th>\n",
       "      <th>occupation_other_service</th>\n",
       "      <th>occupation_priv_house_serv</th>\n",
       "      <th>occupation_prof_specialty</th>\n",
       "      <th>occupation_protective_serv</th>\n",
       "      <th>occupation_sales</th>\n",
       "      <th>occupation_tech_support</th>\n",
       "      <th>occupation_transport_moving</th>\n",
       "      <th>relationship_husband</th>\n",
       "      <th>relationship_not_in_family</th>\n",
       "      <th>relationship_other_relative</th>\n",
       "      <th>relationship_own_child</th>\n",
       "      <th>relationship_unmarried</th>\n",
       "      <th>relationship_wife</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.301</td>\n",
       "      <td>0.800</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.398</td>\n",
       "      <td>1</td>\n",
       "      <td>0.063</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.452</td>\n",
       "      <td>0.800</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.122</td>\n",
       "      <td>1</td>\n",
       "      <td>0.042</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.288</td>\n",
       "      <td>0.533</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.398</td>\n",
       "      <td>1</td>\n",
       "      <td>0.042</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.493</td>\n",
       "      <td>0.400</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.398</td>\n",
       "      <td>1</td>\n",
       "      <td>0.042</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.151</td>\n",
       "      <td>0.800</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.398</td>\n",
       "      <td>0</td>\n",
       "      <td>0.042</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     age  education_num  race  gender  hours_per_week  native_country  \\\n",
       "0  0.301          0.800     1       1           0.398               1   \n",
       "1  0.452          0.800     1       1           0.122               1   \n",
       "2  0.288          0.533     1       1           0.398               1   \n",
       "3  0.493          0.400     0       1           0.398               1   \n",
       "4  0.151          0.800     0       0           0.398               0   \n",
       "\n",
       "   capital  workclass_federal_gov  workclass_local_gov  workclass_private  \\\n",
       "0    0.063                      0                    0                  0   \n",
       "1    0.042                      0                    0                  0   \n",
       "2    0.042                      0                    0                  1   \n",
       "3    0.042                      0                    0                  1   \n",
       "4    0.042                      0                    0                  1   \n",
       "\n",
       "   workclass_self_emp_inc  workclass_self_emp_not_inc  workclass_state_gov  \\\n",
       "0                       0                           0                    1   \n",
       "1                       0                           1                    0   \n",
       "2                       0                           0                    0   \n",
       "3                       0                           0                    0   \n",
       "4                       0                           0                    0   \n",
       "\n",
       "   workclass_without_pay  marital_status_divorced  \\\n",
       "0                      0                        0   \n",
       "1                      0                        0   \n",
       "2                      0                        1   \n",
       "3                      0                        0   \n",
       "4                      0                        0   \n",
       "\n",
       "   marital_status_married_af_spouse  marital_status_married_civ_spouse  \\\n",
       "0                                 0                                  0   \n",
       "1                                 0                                  1   \n",
       "2                                 0                                  0   \n",
       "3                                 0                                  1   \n",
       "4                                 0                                  1   \n",
       "\n",
       "   marital_status_married_spouse_absent  marital_status_never_married  \\\n",
       "0                                     0                             1   \n",
       "1                                     0                             0   \n",
       "2                                     0                             0   \n",
       "3                                     0                             0   \n",
       "4                                     0                             0   \n",
       "\n",
       "   marital_status_separated  marital_status_widowed  occupation_adm_clerical  \\\n",
       "0                         0                       0                        1   \n",
       "1                         0                       0                        0   \n",
       "2                         0                       0                        0   \n",
       "3                         0                       0                        0   \n",
       "4                         0                       0                        0   \n",
       "\n",
       "   occupation_armed_forces  occupation_craft_repair  \\\n",
       "0                        0                        0   \n",
       "1                        0                        0   \n",
       "2                        0                        0   \n",
       "3                        0                        0   \n",
       "4                        0                        0   \n",
       "\n",
       "   occupation_exec_managerial  occupation_farming_fishing  \\\n",
       "0                           0                           0   \n",
       "1                           1                           0   \n",
       "2                           0                           0   \n",
       "3                           0                           0   \n",
       "4                           0                           0   \n",
       "\n",
       "   occupation_handlers_cleaners  occupation_machine_op_inspct  \\\n",
       "0                             0                             0   \n",
       "1                             0                             0   \n",
       "2                             1                             0   \n",
       "3                             1                             0   \n",
       "4                             0                             0   \n",
       "\n",
       "   occupation_other_service  occupation_priv_house_serv  \\\n",
       "0                         0                           0   \n",
       "1                         0                           0   \n",
       "2                         0                           0   \n",
       "3                         0                           0   \n",
       "4                         0                           0   \n",
       "\n",
       "   occupation_prof_specialty  occupation_protective_serv  occupation_sales  \\\n",
       "0                          0                           0                 0   \n",
       "1                          0                           0                 0   \n",
       "2                          0                           0                 0   \n",
       "3                          0                           0                 0   \n",
       "4                          1                           0                 0   \n",
       "\n",
       "   occupation_tech_support  occupation_transport_moving  relationship_husband  \\\n",
       "0                        0                            0                     0   \n",
       "1                        0                            0                     1   \n",
       "2                        0                            0                     0   \n",
       "3                        0                            0                     1   \n",
       "4                        0                            0                     0   \n",
       "\n",
       "   relationship_not_in_family  relationship_other_relative  \\\n",
       "0                           1                            0   \n",
       "1                           0                            0   \n",
       "2                           1                            0   \n",
       "3                           0                            0   \n",
       "4                           0                            0   \n",
       "\n",
       "   relationship_own_child  relationship_unmarried  relationship_wife  target  \n",
       "0                       0                       0                  0       0  \n",
       "1                       0                       0                  0       0  \n",
       "2                       0                       0                  0       0  \n",
       "3                       0                       0                  0       0  \n",
       "4                       0                       0                  1       0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import io\n",
    "import requests\n",
    "\n",
    "# so that we can see all the columns\n",
    "pd.set_option('display.max_columns', None) \n",
    "\n",
    "df_url = 'https://raw.githubusercontent.com/akmand/datasets/master/us_census_income_data_clean_encoded.csv'\n",
    "url_content = requests.get(df_url, verify=False).content\n",
    "df = pd.read_csv(io.StringIO(url_content.decode('utf-8')))\n",
    "\n",
    "# df = pd.read_csv('us_census_income_data_clean_encoded.csv')\n",
    "\n",
    "print(df.shape)\n",
    "df.head().round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5000, 42)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sample = df.sample(n=num_samples, random_state=999).reset_index(drop=True)\n",
    "\n",
    "df_sample.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "target = df_sample['target']\n",
    "Data_df = df_sample.drop(columns = 'target')\n",
    "Data_numpy = Data_df.values\n",
    "D_train, D_test, t_train, t_test = train_test_split(Data_numpy, \n",
    "                                                    target.values, \n",
    "                                                    shuffle=True,\n",
    "                                                    test_size=0.3, \n",
    "                                                    random_state=999)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise 1\n",
    "\n",
    "Determine the most important 10 features as selected by Random Forest Importance (RFI) using the **training** data and visualize them.\n",
    "\n",
    "In the rest of these exercises, you will use these selected features and not the whole set of descriptive features. You can achieve this as below:\n",
    "```Python\n",
    "D_Train_fs = D_train[:, fs_indices_rfi]\n",
    "D_Test_fs  = D_test[:, fs_indices_rfi]\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['age', 'capital', 'education_num', 'hours_per_week',\n",
       "       'marital_status_married_civ_spouse', 'relationship_husband',\n",
       "       'occupation_exec_managerial', 'marital_status_never_married',\n",
       "       'occupation_prof_specialty', 'gender'], dtype=object)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "num_features = 10\n",
    "model_rfi = RandomForestClassifier(n_estimators=100, random_state=999)\n",
    "model_rfi.fit(Data_numpy, target)\n",
    "fs_indices_rfi = np.argsort(model_rfi.feature_importances_)[::-1][0:num_features]\n",
    "\n",
    "best_features_rfi = Data_df.columns[fs_indices_rfi].values\n",
    "best_features_rfi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.21631283, 0.13899253, 0.13141843, 0.10456133, 0.08193192,\n",
       "       0.0476534 , 0.02514301, 0.02180854, 0.01912856, 0.01692581])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_importances_rfi = model_rfi.feature_importances_[fs_indices_rfi]\n",
    "feature_importances_rfi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline \n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "plt.style.use(\"seaborn\")\n",
    "\n",
    "def plot_imp(best_features, scores, method_name):   \n",
    "    plt.barh(best_features, scores)\n",
    "    plt.title(method_name + ' Feature Importances')\n",
    "    plt.xlabel(\"Importance\")\n",
    "    plt.ylabel(\"Features\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 358,
       "width": 639
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_imp(best_features_rfi, feature_importances_rfi, 'Random Forest')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from this point forward, we will only work with the selected features\n",
    "D_Train_fs = D_train[:, fs_indices_rfi]\n",
    "D_Test_fs  = D_test[:, fs_indices_rfi]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise 2\n",
    "\n",
    "Fit and fine-tune a KNN model using the **train** data. For fine-tuning, consider K values in {1, 5, 10, 15, 20} and p values in {1, 2}. Also visualize the tuning results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import StratifiedKFold, GridSearchCV\n",
    "\n",
    "cv_method_train = StratifiedKFold(n_splits=5, shuffle=True, random_state=999)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "params_KNN = {'n_neighbors': [1, 5, 10, 15, 20, 25, 30], 'p': [1, 2]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "gs_KNN = GridSearchCV(estimator=KNeighborsClassifier(), \n",
    "                      param_grid=params_KNN, \n",
    "                      cv=cv_method_train,\n",
    "                      verbose=1,\n",
    "                      scoring=scoring_metric)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 14 candidates, totalling 70 fits\n"
     ]
    }
   ],
   "source": [
    "gs_KNN.fit(D_Train_fs, t_train);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'n_neighbors': 30, 'p': 1}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gs_KNN.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8692219679655728"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gs_KNN.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.69541487, 0.70190213, 0.83482606, 0.83603535, 0.85964085,\n",
       "       0.85958014, 0.86577897, 0.86489486, 0.86791486, 0.86548364,\n",
       "       0.86856082, 0.86698149, 0.86922197, 0.86660173])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To extract more cross-validation results, we can call gs.csv_results \n",
    "# - a dictionary consisting of run details for each fold.\n",
    "gs_KNN.cv_results_['mean_test_score']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "results_KNN = pd.DataFrame(gs_KNN.cv_results_['params'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "results_KNN['test_score'] = gs_KNN.cv_results_['mean_test_score']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>n_neighbors</th>\n",
       "      <th>p</th>\n",
       "      <th>test_score</th>\n",
       "      <th>metric</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.695415</td>\n",
       "      <td>Manhattan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.701902</td>\n",
       "      <td>Euclidean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0.834826</td>\n",
       "      <td>Manhattan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0.836035</td>\n",
       "      <td>Euclidean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0.859641</td>\n",
       "      <td>Manhattan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>0.859580</td>\n",
       "      <td>Euclidean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>0.865779</td>\n",
       "      <td>Manhattan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>0.864895</td>\n",
       "      <td>Euclidean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>0.867915</td>\n",
       "      <td>Manhattan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>0.865484</td>\n",
       "      <td>Euclidean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>0.868561</td>\n",
       "      <td>Manhattan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>0.866981</td>\n",
       "      <td>Euclidean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "      <td>0.869222</td>\n",
       "      <td>Manhattan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>30</td>\n",
       "      <td>2</td>\n",
       "      <td>0.866602</td>\n",
       "      <td>Euclidean</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    n_neighbors  p  test_score     metric\n",
       "0             1  1    0.695415  Manhattan\n",
       "1             1  2    0.701902  Euclidean\n",
       "2             5  1    0.834826  Manhattan\n",
       "3             5  2    0.836035  Euclidean\n",
       "4            10  1    0.859641  Manhattan\n",
       "5            10  2    0.859580  Euclidean\n",
       "6            15  1    0.865779  Manhattan\n",
       "7            15  2    0.864895  Euclidean\n",
       "8            20  1    0.867915  Manhattan\n",
       "9            20  2    0.865484  Euclidean\n",
       "10           25  1    0.868561  Manhattan\n",
       "11           25  2    0.866981  Euclidean\n",
       "12           30  1    0.869222  Manhattan\n",
       "13           30  2    0.866602  Euclidean"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_KNN['metric'] = results_KNN['p'].replace([1,2], [\"Manhattan\", \"Euclidean\"])\n",
    "results_KNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 358,
       "width": 506
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in [\"Manhattan\", \"Euclidean\"]:\n",
    "    temp = results_KNN[results_KNN['metric'] == i]\n",
    "    plt.plot(temp['n_neighbors'], temp['test_score'], marker = '.', label = i)\n",
    "    \n",
    "plt.legend()\n",
    "plt.xlabel('Number of Neighbors')\n",
    "plt.ylabel(\"Mean CV Score\")\n",
    "plt.title(\"KNN Performance Comparison\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise 3\n",
    "\n",
    "Fit and fine-tune a DT model using the **train** data. For fine-tuning, consider max_depth values in {3, 5, 7, 10, 12} and min_samples_split values in {2, 5, 15, 20, 25}. Also visualize the tuning results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 25 candidates, totalling 125 fits\n"
     ]
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "df_classifier = DecisionTreeClassifier(random_state=999)\n",
    "\n",
    "params_DT = {'max_depth': [3, 5, 7, 10, 12],\n",
    "             'min_samples_split': [2, 5, 15, 20, 25]}\n",
    "            \n",
    "gs_DT = GridSearchCV(estimator=df_classifier, \n",
    "                     param_grid=params_DT, \n",
    "                     cv=cv_method_train,\n",
    "                     verbose=1, \n",
    "                     scoring=scoring_metric)\n",
    "\n",
    "gs_DT.fit(D_Train_fs, t_train);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'max_depth': 7, 'min_samples_split': 5}"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gs_DT.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8862641529718823"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gs_DT.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['max_depth', 'min_samples_split', 'test_score'], dtype='object')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's define a new data frame to store the DT grid search results for visualization.\n",
    "results_DT = pd.DataFrame(gs_DT.cv_results_['params'])\n",
    "results_DT['test_score'] = gs_DT.cv_results_['mean_test_score']\n",
    "results_DT.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 358,
       "width": 501
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in [2, 5, 15, 20, 25]:\n",
    "    temp = results_DT[results_DT['min_samples_split'] == i]\n",
    "    temp_average = temp.groupby('max_depth').agg({'test_score': 'mean'})\n",
    "    plt.plot(temp_average, marker = '.', label = 'min sample split: ' + str(i))\n",
    "    \n",
    "    \n",
    "plt.legend()\n",
    "plt.xlabel('Max Depth')\n",
    "plt.ylabel(\"Mean CV Score\")\n",
    "plt.title(\"DT Performance Comparison\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise 4\n",
    "\n",
    "Fit and fine-tune a NB model using the **train** data. For fine-tuning, consider var_smoothing values in `np.logspace(1,-2, num=50)`. Also visualize the tuning results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 50 candidates, totalling 250 fits\n"
     ]
    }
   ],
   "source": [
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.preprocessing import PowerTransformer\n",
    "\n",
    "nb_classifier = GaussianNB()\n",
    "\n",
    "params_NB = {'var_smoothing': np.logspace(1,-2, num=50)}\n",
    "\n",
    "gs_NB = GridSearchCV(estimator=nb_classifier, \n",
    "                     param_grid=params_NB, \n",
    "                     cv=cv_method_train,\n",
    "                     verbose=1, \n",
    "                     scoring=scoring_metric)\n",
    "\n",
    "D_Train_fs_transformed = PowerTransformer().fit_transform(D_Train_fs)\n",
    "\n",
    "gs_NB.fit(D_Train_fs_transformed, t_train);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'var_smoothing': 0.3906939937054617}"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gs_NB.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8866679203784997"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gs_NB.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let's define a new data frame to store the NB grid search results for visualization\n",
    "results_NB = pd.DataFrame(gs_NB.cv_results_['params'])\n",
    "results_NB['test_score'] = gs_NB.cv_results_['mean_test_score']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 358,
       "width": 506
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(results_NB['var_smoothing'], results_NB['test_score'], marker = '.')    \n",
    "plt.xlabel('Var. Smoothing')\n",
    "plt.ylabel(\"Mean CV Score\")\n",
    "plt.title(\"NB Performance Comparison\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise 5\n",
    "\n",
    "Fit and fine-tune a Random Forest model using the **train** data. For fine-tuning, consider n_estimators values in {100, 250, 500} and max_depth values in {3, 5, 7, 10, 12}. Also visualize the tuning results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 12 candidates, totalling 60 fits\n"
     ]
    }
   ],
   "source": [
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.preprocessing import PowerTransformer\n",
    "\n",
    "rf_classifier = RandomForestClassifier(random_state=999)\n",
    "\n",
    "params_RF = {'n_estimators': [100, 250, 500],\n",
    "             'max_depth': [5, 7, 10, 12]}\n",
    "\n",
    "gs_RF = GridSearchCV(estimator=rf_classifier, \n",
    "                     param_grid=params_RF, \n",
    "                     cv=cv_method_train,\n",
    "                     verbose=1,\n",
    "                     n_jobs=-2,\n",
    "                     scoring=scoring_metric)\n",
    "\n",
    "gs_RF.fit(D_Train_fs, t_train);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'max_depth': 7, 'n_estimators': 250}"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gs_RF.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9068092192464776"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gs_RF.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['max_depth', 'n_estimators', 'test_score'], dtype='object')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's define a new data frame to store the grid search results for visualization.\n",
    "results_RF = pd.DataFrame(gs_RF.cv_results_['params'])\n",
    "results_RF['test_score'] = gs_RF.cv_results_['mean_test_score']\n",
    "results_RF.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 358,
       "width": 506
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in results_RF['n_estimators'].unique():\n",
    "    temp = results_RF[results_RF['n_estimators'] == i]\n",
    "    plt.plot(temp['max_depth'], temp['test_score'], marker = '.', label = 'estimators: ' + str(i))\n",
    "    \n",
    "plt.legend()\n",
    "plt.xlabel('Max Depth')\n",
    "plt.ylabel(\"Mean CV Score\")\n",
    "plt.title(\"RF Performance Comparison\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise 6\n",
    "\n",
    "What we would like to do now is to \"fit\" each tuned classifier (with their best set of hyperparameter values) on the **test** data in a cross-validated fashion to figure out which (tuned) classifier performs the best. This way, we will be measuring performance of the tuned classifiers on data that they did not \"see\" previously.\n",
    "\n",
    "Since cross validation itself is a random process, we would like to perform pairwise t-tests to determine if any difference between the performance of any two (tuned) classifiers is statistically significant. Specifically, we first perform 5-fold stratified cross-validation (without any repetitions) on each (tuned) classifier where we use the same seed in each of the four cross-validation runs. Second, we conduct a paired t-test for the AUC score between the following (tuned) classifier combinations.\n",
    "\n",
    "For this question, perform the procedures discussed above and decide if any one the tuned classifiers is statistically better than the rest at a 95% significance level."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "cv_method_test = StratifiedKFold(n_splits=5, shuffle=True, random_state=999)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8698548148148149"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cv_results_KNN = cross_val_score(estimator=gs_KNN.best_estimator_,\n",
    "                                 X=D_Test_fs,\n",
    "                                 y=t_test, \n",
    "                                 cv=cv_method_test, \n",
    "                                 scoring='roc_auc')\n",
    "cv_results_KNN.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8579674074074074"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cv_results_DT = cross_val_score(estimator=gs_DT.best_estimator_,\n",
    "                                 X=D_Test_fs,\n",
    "                                 y=t_test, \n",
    "                                 cv=cv_method_test, \n",
    "                                 scoring='roc_auc')\n",
    "cv_results_DT.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8966044444444445"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make sure you don't forget the power transformation\n",
    "\n",
    "D_Test_fs_transformed = PowerTransformer().fit_transform(D_Test_fs)\n",
    "\n",
    "cv_results_NB = cross_val_score(estimator=gs_NB.best_estimator_,\n",
    "                                 X=D_Test_fs_transformed,\n",
    "                                 y=t_test, \n",
    "                                 cv=cv_method_test, \n",
    "                                 scoring='roc_auc')\n",
    "cv_results_NB.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9081125925925926"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cv_results_RF = cross_val_score(estimator=gs_RF.best_estimator_,\n",
    "                                 X=D_Test_fs,\n",
    "                                 y=t_test, \n",
    "                                 cv=cv_method_test, \n",
    "                                 n_jobs=-2,\n",
    "                                 scoring='roc_auc')\n",
    "cv_results_RF.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ttest_relResult(statistic=7.815450855150375, pvalue=0.001446641754333493)\n",
      "Ttest_relResult(statistic=4.369008643730098, pvalue=0.011977362937008334)\n",
      "Ttest_relResult(statistic=1.6818508719146943, pvalue=0.16788992249462276)\n"
     ]
    }
   ],
   "source": [
    "from scipy import stats\n",
    "\n",
    "# RF seems to be the best, so let's compare that to the others\n",
    "# any p-value < 0.05 indicates a statistically significant result\n",
    "\n",
    "print(stats.ttest_rel(cv_results_RF, cv_results_KNN))\n",
    "print(stats.ttest_rel(cv_results_RF, cv_results_DT))\n",
    "print(stats.ttest_rel(cv_results_RF, cv_results_NB))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise 7\n",
    "\n",
    "Rerun your notebook with different number of features (e.g., 5, 15, 20). Also try with no feature selection at all (set num_features=41).\n",
    "Comment if your results improve. Which number of features seem to work best?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Optional: beyond two hyper-parameters\n",
    "\n",
    "In previous exercises, we have created a decision tree and a random forest. For these models, we \"tuned\" up to two hyper-parameters. Sometimes two parameters are not sufficient. We need more! In this optional exercise, we will illustrate how to go beyond tuning more than two hyper parameters of a random forest. In particular, we would like to assess if the performance would improve when entropy is used instead of gini. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'bootstrap': True,\n",
       " 'ccp_alpha': 0.0,\n",
       " 'class_weight': None,\n",
       " 'criterion': 'gini',\n",
       " 'max_depth': None,\n",
       " 'max_features': 'auto',\n",
       " 'max_leaf_nodes': None,\n",
       " 'max_samples': None,\n",
       " 'min_impurity_decrease': 0.0,\n",
       " 'min_impurity_split': None,\n",
       " 'min_samples_leaf': 1,\n",
       " 'min_samples_split': 2,\n",
       " 'min_weight_fraction_leaf': 0.0,\n",
       " 'n_estimators': 100,\n",
       " 'n_jobs': None,\n",
       " 'oob_score': False,\n",
       " 'random_state': 999,\n",
       " 'verbose': 0,\n",
       " 'warm_start': False}"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf_classifier = RandomForestClassifier(random_state=999)\n",
    "\n",
    "# Obtain the parameters\n",
    "rf_classifier.get_params()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 42 candidates, totalling 210 fits\n"
     ]
    }
   ],
   "source": [
    "params_RF = {'n_estimators': [100, 250, 500],\n",
    "             'max_depth': np.arange(5, 12),\n",
    "             'criterion': ['gini', 'entropy']}\n",
    "\n",
    "gs_RF = GridSearchCV(estimator=rf_classifier, \n",
    "                     param_grid=params_RF, \n",
    "                     cv=cv_method_train,\n",
    "                     verbose=1,\n",
    "                     n_jobs=-2,\n",
    "                     scoring=scoring_metric)\n",
    "\n",
    "gs_RF.fit(D_Train_fs, t_train);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "rf_results = pd.DataFrame.from_dict(gs_RF.cv_results_['params'])\n",
    "rf_results['score'] = gs_RF.cv_results_['mean_test_score']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 786x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 356,
       "width": 779
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "rel_plot = sns.relplot(\n",
    "    data=rf_results, x=\"max_depth\", y=\"score\",\n",
    "    col=\"criterion\", hue=\"n_estimators\", style=\"n_estimators\",\n",
    "    kind=\"line\"\n",
    ")\n",
    "rel_plot.axes[0,0].set_xlabel('Max depth')\n",
    "rel_plot.axes[0,1].set_xlabel('Max depth')\n",
    "rel_plot.axes[0,0].set_ylabel('Score')\n",
    "rel_plot._legend.set_title(\"Number of\\nestimators\")\n",
    "rel_plot._legend._legend_box.align = \"left\"\n",
    "rel_plot.fig.subplots_adjust(top=0.8)\n",
    "rel_plot.fig.suptitle('Random forest performance', fontsize=16)\n",
    "plt.show(rel_plot)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Optional: imbalanced class mitigation in hyper-parameter tuning\n",
    "\n",
    "Sometimes, a classification problem might have \"imbalanced class issue\" - that is one of the target labels is a \"minority class\". For example, the income data has 25 % of instances earning more than USD 50,000 (positive label). There are many approaches to mitigate the imbalanced class. One is to adopt the appropriate metrics. We have been using ROC as the scoring metric as it can balance the true positive rate (TPR) and the true negative rate (TNR). Another approach is to impose \"class weight\" during hyper-parameter tuning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0, 1], dtype=int64), array([1125,  375], dtype=int64))"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(t_test, return_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.87      0.94      0.91      1125\n",
      "           1       0.78      0.59      0.67       375\n",
      "\n",
      "    accuracy                           0.86      1500\n",
      "   macro avg       0.83      0.77      0.79      1500\n",
      "weighted avg       0.85      0.86      0.85      1500\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "t_pred = gs_RF.predict(D_Test_fs)\n",
    "print(classification_report(t_test, t_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 63 candidates, totalling 315 fits\n"
     ]
    }
   ],
   "source": [
    "rf_classifier_wgt = RandomForestClassifier(random_state=999, criterion='entropy')\n",
    "params_RF_wgt = {'n_estimators': [100, 250, 500],\n",
    "                 'max_depth': np.arange(5, 12),\n",
    "                 'class_weight': [{0:1, 1:1}, {0:1, 1:3}, {0:1, 1:4}]}\n",
    "\n",
    "gs_RF_wgt = GridSearchCV(estimator=rf_classifier_wgt, \n",
    "                         param_grid=params_RF_wgt, \n",
    "                         cv=cv_method_train,\n",
    "                         verbose=1,\n",
    "                         n_jobs=-2,\n",
    "                         scoring=scoring_metric)\n",
    "\n",
    "gs_RF_wgt.fit(D_Train_fs, t_train);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'class_weight': {0: 1, 1: 1}, 'max_depth': 8, 'n_estimators': 500}"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gs_RF_wgt.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.87      0.94      0.90      1125\n",
      "           1       0.77      0.56      0.65       375\n",
      "\n",
      "    accuracy                           0.85      1500\n",
      "   macro avg       0.82      0.75      0.78      1500\n",
      "weighted avg       0.84      0.85      0.84      1500\n",
      "\n"
     ]
    }
   ],
   "source": [
    "t_pred_wgt = gs_RF_wgt.predict(D_Test_fs)\n",
    "print(classification_report(t_test, t_pred_wgt))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "www.featureranking.com"
   ]
  }
 ],
 "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": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}