model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 421,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>hashtags</th>\n",
       "      <th>labels</th>\n",
       "      <th>Column1</th>\n",
       "      <th>_1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Being s mom is cleaning 24/7 the same shit ove...</td>\n",
       "      <td>['momlife', 'kids', 'tired']</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>And now we have been given the walkthru book b...</td>\n",
       "      <td>['walkthru']</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Wishing YOU Peace Joy &amp; Love! JoyTrain MentalH...</td>\n",
       "      <td>['Peace', 'Joy', 'Love', 'JoyTrain', 'MentalHe...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>speak-no-evil monkey Can I Be Honest With You...</td>\n",
       "      <td>['therapy', 'help', 'NLP', 'CBT', 'hypnotherap...</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Psy Do u hv any regrets? Me No Psy Are you hap...</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                text  \\\n",
       "0  Being s mom is cleaning 24/7 the same shit ove...   \n",
       "1  And now we have been given the walkthru book b...   \n",
       "2  Wishing YOU Peace Joy & Love! JoyTrain MentalH...   \n",
       "3   speak-no-evil monkey Can I Be Honest With You...   \n",
       "4  Psy Do u hv any regrets? Me No Psy Are you hap...   \n",
       "\n",
       "                                            hashtags  labels  Column1  _1  \n",
       "0                       ['momlife', 'kids', 'tired']       1      NaN NaN  \n",
       "1                                       ['walkthru']       0      NaN NaN  \n",
       "2  ['Peace', 'Joy', 'Love', 'JoyTrain', 'MentalHe...       0      NaN NaN  \n",
       "3  ['therapy', 'help', 'NLP', 'CBT', 'hypnotherap...       1      NaN NaN  \n",
       "4                                                 []       0      NaN NaN  "
      ]
     },
     "execution_count": 421,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel(\"data/twitter_stress.xlsx\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 422,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan])"
      ]
     },
     "execution_count": 422,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Column1'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 423,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan])"
      ]
     },
     "execution_count": 423,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['_1'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 424,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(labels=['Column1', '_1'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 425,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>Being s mom is cleaning 24/7 the same shit ove...</td>\n",
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       "      <th>1</th>\n",
       "      <td>And now we have been given the walkthru book b...</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Wishing YOU Peace Joy &amp; Love! JoyTrain MentalH...</td>\n",
       "      <td>['Peace', 'Joy', 'Love', 'JoyTrain', 'MentalHe...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>speak-no-evil monkey Can I Be Honest With You...</td>\n",
       "      <td>['therapy', 'help', 'NLP', 'CBT', 'hypnotherap...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Psy Do u hv any regrets? Me No Psy Are you hap...</td>\n",
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       "      <td>0</td>\n",
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      "text/plain": [
       "                                                text  \\\n",
       "0  Being s mom is cleaning 24/7 the same shit ove...   \n",
       "1  And now we have been given the walkthru book b...   \n",
       "2  Wishing YOU Peace Joy & Love! JoyTrain MentalH...   \n",
       "3   speak-no-evil monkey Can I Be Honest With You...   \n",
       "4  Psy Do u hv any regrets? Me No Psy Are you hap...   \n",
       "\n",
       "                                            hashtags  labels  \n",
       "0                       ['momlife', 'kids', 'tired']       1  \n",
       "1                                       ['walkthru']       0  \n",
       "2  ['Peace', 'Joy', 'Love', 'JoyTrain', 'MentalHe...       0  \n",
       "3  ['therapy', 'help', 'NLP', 'CBT', 'hypnotherap...       1  \n",
       "4                                                 []       0  "
      ]
     },
     "execution_count": 425,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 426,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([\"['momlife', 'kids', 'tired']\", \"['walkthru']\",\n",
       "       \"['Peace', 'Joy', 'Love', 'JoyTrain', 'MentalHealth', 'Quote', 'Mindfulness', 'GoldenHearts', 'IAM', 'ChooseLove']\",\n",
       "       ..., \"['m1hl', 'stress', 'technostress', 'tips']\",\n",
       "       \"['DogsofTwittter', 'shout', 'getoutforshout', 'charity', 'charitywalk', 'mentalhealth', 'MentalHealthMatters', 'September']\",\n",
       "       \"['funny', 'tired', 'girldad']\"], dtype=object)"
      ]
     },
     "execution_count": 426,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['hashtags'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 427,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 428,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop_duplicates(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 429,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>hashtags</th>\n",
       "      <th>labels</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Being s mom is cleaning 247 the same shit over...</td>\n",
       "      <td>momlife kids tired</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>And now we have been given the walkthru book b...</td>\n",
       "      <td>walkthru</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Wishing YOU Peace Joy  Love JoyTrain MentalHea...</td>\n",
       "      <td>Peace Joy Love JoyTrain MentalHealth Quote Min...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>speaknoevil monkey Can I Be Honest With You g...</td>\n",
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      "text/plain": [
       "                                                text  \\\n",
       "0  Being s mom is cleaning 247 the same shit over...   \n",
       "1  And now we have been given the walkthru book b...   \n",
       "2  Wishing YOU Peace Joy  Love JoyTrain MentalHea...   \n",
       "3   speaknoevil monkey Can I Be Honest With You g...   \n",
       "4  Psy Do u hv any regrets Me No Psy Are you happ...   \n",
       "\n",
       "                                            hashtags  labels  \n",
       "0                                 momlife kids tired       1  \n",
       "1                                           walkthru       0  \n",
       "2  Peace Joy Love JoyTrain MentalHealth Quote Min...       0  \n",
       "3  therapy help NLP CBT hypnotherapy mentalhealth...       1  \n",
       "4                                                          0  "
      ]
     },
     "execution_count": 429,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove the special characters from the text\n",
    "import re\n",
    "def remove_special_char(text):\n",
    "    pattern = r'[^\\w\\s]|[\\n\\t\\r]'\n",
    "    return re.sub(pattern, '', text)\n",
    "\n",
    "df['hashtags'] = df['hashtags'].apply(remove_special_char)\n",
    "df['text'] = df['text'].apply(remove_special_char)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     C:\\Users\\kamal\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n",
      "[nltk_data] Downloading package punkt to\n",
      "[nltk_data]     C:\\Users\\kamal\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package punkt is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 430,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import nltk\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.tokenize import word_tokenize\n",
    "nltk.download('stopwords')\n",
    "nltk.download('punkt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 431,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mom cleaning 247 shit end result everything mess momlife kids tired\n"
     ]
    }
   ],
   "source": [
    "stop_words = set(stopwords.words('english'))\n",
    "\n",
    "def remove_stop_words(text):\n",
    "    tokens = word_tokenize(text)\n",
    "    filt_text = [word for word in tokens if word.lower() not in stop_words]\n",
    "    return ' '.join (filt_text)\n",
    "\n",
    "df['text'] = df['text'].apply(remove_stop_words)\n",
    "df['hashtags'] = df['hashtags'].apply(remove_stop_words)\n",
    "print(df['text'][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 432,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<bound method NDFrame.describe of                                                    text  \\\n",
      "0     mom cleaning 247 shit end result everything me...   \n",
      "1     given walkthru book base whole school PD grinn...   \n",
      "2     Wishing Peace Joy Love JoyTrain MentalHealth Q...   \n",
      "3     speaknoevil monkey Honest globe showing Europe...   \n",
      "4     Psy u hv regrets Psy happy Yes feel relieved G...   \n",
      "...                                                 ...   \n",
      "8895  Thank business questions today Selfgenerated b...   \n",
      "8896  planning walking minds today woman walking red...   \n",
      "8897  mobile phones Three Tips Reduce Technostress k...   \n",
      "8898  purple heart Day 1 purple heart vets first Dog...   \n",
      "8899  exactly Bella last night also favorite episode...   \n",
      "\n",
      "                                               hashtags  labels  \n",
      "0                                    momlife kids tired       1  \n",
      "1                                              walkthru       0  \n",
      "2     Peace Joy Love JoyTrain MentalHealth Quote Min...       0  \n",
      "3     therapy help NLP CBT hypnotherapy mentalhealth...       1  \n",
      "4                                                             0  \n",
      "...                                                 ...     ...  \n",
      "8895                 business business Stress mind body       0  \n",
      "8896  walkthemind walking walk hiking mentalhealth M...       1  \n",
      "8897                      m1hl stress technostress tips       1  \n",
      "8898  DogsofTwittter shout getoutforshout charity ch...       1  \n",
      "8899                                funny tired girldad       1  \n",
      "\n",
      "[8516 rows x 3 columns]>\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 8516 entries, 0 to 8899\n",
      "Data columns (total 3 columns):\n",
      " #   Column    Non-Null Count  Dtype \n",
      "---  ------    --------------  ----- \n",
      " 0   text      8516 non-null   object\n",
      " 1   hashtags  8516 non-null   object\n",
      " 2   labels    8516 non-null   int64 \n",
      "dtypes: int64(1), object(2)\n",
      "memory usage: 524.2+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(df.describe)\n",
    "print(df.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 433,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 8467 entries, 0 to 8899\n",
      "Data columns (total 3 columns):\n",
      " #   Column    Non-Null Count  Dtype \n",
      "---  ------    --------------  ----- \n",
      " 0   text      8467 non-null   object\n",
      " 1   hashtags  8467 non-null   object\n",
      " 2   labels    8467 non-null   int64 \n",
      "dtypes: int64(1), object(2)\n",
      "memory usage: 264.6+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "df.drop_duplicates(inplace=True)\n",
    "print(df.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 434,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 435,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_text = df.iloc[:,0]\n",
    "x_hash = df.iloc[:,1]\n",
    "y = df['labels']\n",
    "x_text_train, x_text_test, x_hash_train, x_hash_test, y_train, y_test = train_test_split(x_text, x_hash, y, test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 526,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import AdaBoostClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 532,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating pipeline for text data\n",
    "text_pipeline = Pipeline([\n",
    "    ('vect', CountVectorizer(lowercase=True, stop_words = 'english', max_df = 0.80, ngram_range=(1,3))),\n",
    "    ('clf', AdaBoostClassifier(estimator = LogisticRegression(C=2, max_iter=8000, solver=\"saga\", penalty='l2', n_jobs=-1, random_state=42)))\n",
    "])\n",
    "\n",
    "# Creating pipeline for hash data\n",
    "hash_pipeline = Pipeline([\n",
    "    ('vect', CountVectorizer(lowercase=True, max_df = 0.80, ngram_range=(1,1))),\n",
    "    ('clf', AdaBoostClassifier(estimator = LogisticRegression(C=2, max_iter=8000, solver=\"saga\", penalty='l2', n_jobs=-1, random_state=42)))\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 534,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "f:\\data-science\\Projects\\is-stress\\venv\\lib\\site-packages\\sklearn\\ensemble\\_weight_boosting.py:519: FutureWarning: The SAMME.R algorithm (the default) is deprecated and will be removed in 1.6. Use the SAMME algorithm to circumvent this warning.\n",
      "  warnings.warn(\n",
      "f:\\data-science\\Projects\\is-stress\\venv\\lib\\site-packages\\sklearn\\ensemble\\_weight_boosting.py:519: FutureWarning: The SAMME.R algorithm (the default) is deprecated and will be removed in 1.6. Use the SAMME algorithm to circumvent this warning.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-9 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
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       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-9 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-9 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-9 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-9 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-9 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-9 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-9 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-9 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-9 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-9 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-9 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-9 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-9 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-9 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-9 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-9 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-9 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-9 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-9\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;vect&#x27;, CountVectorizer(max_df=0.8)),\n",
       "                (&#x27;clf&#x27;,\n",
       "                 AdaBoostClassifier(estimator=LogisticRegression(C=2,\n",
       "                                                                 max_iter=8000,\n",
       "                                                                 n_jobs=-1,\n",
       "                                                                 random_state=42,\n",
       "                                                                 solver=&#x27;saga&#x27;)))])</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 fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-23\" type=\"checkbox\" ><label for=\"sk-estimator-id-23\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;vect&#x27;, CountVectorizer(max_df=0.8)),\n",
       "                (&#x27;clf&#x27;,\n",
       "                 AdaBoostClassifier(estimator=LogisticRegression(C=2,\n",
       "                                                                 max_iter=8000,\n",
       "                                                                 n_jobs=-1,\n",
       "                                                                 random_state=42,\n",
       "                                                                 solver=&#x27;saga&#x27;)))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-24\" type=\"checkbox\" ><label for=\"sk-estimator-id-24\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;CountVectorizer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html\">?<span>Documentation for CountVectorizer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>CountVectorizer(max_df=0.8)</pre></div> </div></div><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-25\" type=\"checkbox\" ><label for=\"sk-estimator-id-25\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;clf: AdaBoostClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.ensemble.AdaBoostClassifier.html\">?<span>Documentation for clf: AdaBoostClassifier</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>AdaBoostClassifier(estimator=LogisticRegression(C=2, max_iter=8000, n_jobs=-1,\n",
       "                                                random_state=42,\n",
       "                                                solver=&#x27;saga&#x27;))</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 fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-26\" type=\"checkbox\" ><label for=\"sk-estimator-id-26\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">estimator: LogisticRegression</label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression(C=2, max_iter=8000, n_jobs=-1, random_state=42,\n",
       "                   solver=&#x27;saga&#x27;)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-27\" type=\"checkbox\" ><label for=\"sk-estimator-id-27\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression(C=2, max_iter=8000, n_jobs=-1, random_state=42,\n",
       "                   solver=&#x27;saga&#x27;)</pre></div> </div></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('vect', CountVectorizer(max_df=0.8)),\n",
       "                ('clf',\n",
       "                 AdaBoostClassifier(estimator=LogisticRegression(C=2,\n",
       "                                                                 max_iter=8000,\n",
       "                                                                 n_jobs=-1,\n",
       "                                                                 random_state=42,\n",
       "                                                                 solver='saga')))])"
      ]
     },
     "execution_count": 534,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text_pipeline.fit(x_text_train, y_train)\n",
    "hash_pipeline.fit(x_hash_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 535,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "file = open(\"assets/text_pipeline.pkl\", \"wb\")\n",
    "pickle.dump(text_pipeline, file)\n",
    "file.close()\n",
    "file = open(\"assets/hashtag_pipeline.pkl\", \"wb\")\n",
    "pickle.dump(hash_pipeline, file)\n",
    "file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 536,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_text_pred = text_pipeline.predict(x_text_test)\n",
    "y_hash_pred = hash_pipeline.predict(x_hash_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 537,
   "metadata": {},
   "outputs": [],
   "source": [
    "text_weight = 0.7\n",
    "hash_weight = 0.3\n",
    "\n",
    "final_predictions = text_weight * y_text_pred + hash_weight * y_hash_pred\n",
    "\n",
    "final_predictions = (final_predictions > 0.5).astype(int)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 538,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[563 251]\n",
      " [ 95 785]]\n",
      "0.7957497048406139\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.86      0.69      0.76       814\n",
      "           1       0.76      0.89      0.82       880\n",
      "\n",
      "    accuracy                           0.80      1694\n",
      "   macro avg       0.81      0.79      0.79      1694\n",
      "weighted avg       0.80      0.80      0.79      1694\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score, confusion_matrix, classification_report\n",
    "print(confusion_matrix(y_test, final_predictions))\n",
    "print(accuracy_score(y_test, final_predictions))\n",
    "print(classification_report(y_test, final_predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 539,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The user is stressed\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from wordcloud import WordCloud\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "text_model = pickle.load(open('assets/text_pipeline.pkl', 'rb'))\n",
    "hash_model = pickle.load(open('assets/hashtag_pipeline.pkl', 'rb'))\n",
    "\n",
    "def calculate_prediction(text, hashtag):\n",
    "    text_weight = 0.7\n",
    "    hash_weight = 0.3\n",
    "    final_predictions = text_weight * text + hash_weight * hashtag\n",
    "    final_predictions = (final_predictions > 0.5).astype(int)\n",
    "    return final_predictions\n",
    "\n",
    "\n",
    "def check_if_user_is_stressed(text, hashtag):\n",
    "    \n",
    "    text_predict = text_model.predict(text)\n",
    "    hash_predict = hash_model.predict(hashtag)\n",
    "    outcome = calculate_prediction(text_predict, hash_predict)\n",
    "    if outcome == 1:\n",
    "        outcome = \"stressed\"\n",
    "    else:\n",
    "        outcome = \"not stressed\"\n",
    "    print(f\"The user is {outcome}\")\n",
    "    plot_word_cloud(text[0]+hashtag[0], outcome)\n",
    "\n",
    "def plot_word_cloud(text, title):\n",
    "    wordcloud = WordCloud(width=800, height=400, background_color='white').generate(text)\n",
    "    plt.figure(figsize=(10, 5))\n",
    "    plt.imshow(wordcloud, interpolation='bilinear')\n",
    "    plt.title(title)\n",
    "    plt.axis('off')\n",
    "    plt.show()\n",
    "\n",
    "text = [\"Feeling overwhelmed with everything on my plate right now. Can't seem to catch a break. 😔\"]\n",
    "hashtag = [\"#TooMuchToDo #NeedABreak #Overwhelmed\"]\n",
    "test_outcome = check_if_user_is_stressed(text, hashtag)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 540,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The user is not stressed\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "text = [\"Taking some time to unwind and recharge this weekend. Sometimes you just need to step back and breathe.\"]\n",
    "hashtag = [\"#WeekendVibes #ChillTime #Gratitude #Mindfulness\"]\n",
    "test_outcome = check_if_user_is_stressed(text, hashtag)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.9.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}