ReactionsRegression.ipynb

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    "<h2><B><left>Hello, This Notebook Contains Machine-Learning Service To Training Multioutput Regression Model.</left></B></h2>\n",
    "<h4><I><left>- the produced model is a piece of complement project named(Reactions Prediction).</left></I></h4>\n",
    "<h4><I><left>- We use multioutput regression technique to predict all values by one model insted of train one model per category (there is also mathmatical reasons beyond using it).</left></I></h4>\n",
    "<h4><I><left>- We use Scikit-Learn library for training and testing models.</left></I></h4>\n",
    "<h4><I><left>- We implement different techniques for feature selection, and we use Grid_Search technique for parameters tunning.</left></I></h4>\n",
    "<h4><I><left>- Finally we export the best model into .pickle file</left></I></h4>\n",
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "    <ul>\n",
    "            <li><h3>Contents:</h3></li>\n",
    "   <ul>\n",
    "        <li><h4><a href=\"#exploratory\">Data Exploratory.</a></h4></li>\n",
    "        <li><h4><a href=\"#prep\">Prepocessing.</a></h4></li>\n",
    "        <li><h4><a href=\"#model\">Modeling.</a></h4></li>\n",
    "        <li><h4><a href=\"#results\">Results:</a></h4></li>\n",
    "         <ul>\n",
    "            <li><a href=\"#mse\">compute MSE for multioutput</a></li>\n",
    "            <li><a href=\"#plot\">Plot MSE</a></li>\n",
    "        </ul>\n",
    "       <li><h4><a href=\"#export\">Exporting Model:</a></h4></li>\n",
    "         <ul>\n",
    "            <li><a href=\"#save\">save into pickle</a></li>\n",
    "            <li><a href=\"#test\">test final models</a></li>\n",
    "        </ul>\n",
    "    </ul>\n",
    "    </ul>\n",
    "</div>\n",
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"exploratory\"></a>\n",
    "<h3><B><left>- Data Exploratory:</left></B></h3>\n",
    "</I></h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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       "                                                 content  \\\n",
       "0      امطار  خفيفة تهطل على العاصمة دمشق  عدسة: Nour...   \n",
       "1      . قاعدين بلا شغل وعم نقبض رواتب 🙂.. شو بدنا أح...   \n",
       "2      رادار البروق الآن | زخات مطر مصحوبة بالبروق بد...   \n",
       "3      الشارع يتألم .. لكنه تائه في تحديد الخيارات .....   \n",
       "4             طـــريــقــي My Path 📖📝🎓 ... قريباً جداً 🚦   \n",
       "...                                                  ...   \n",
       "40894  وحدات الهندسة في الجيش العربي السوري تواصل مها...   \n",
       "40895  السيد الرئيس الفريق بشار الأسد يصدر المرسوم ال...   \n",
       "40896  يارب بحق آذان فجر اول يام شهر شعبان اللهم اجعل...   \n",
       "40897  ⭕️رئيس مجلس الشعب يعلن تبلغ المجلس من قبل #الم...   \n",
       "40898  السيد الرئيس الفريق #بشار_الأسد القائد العام ل...   \n",
       "\n",
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       "2                      Hawa Al Sham Weather هوى الشام           163     748.0   \n",
       "3      رفيق نصرالله - المركز الدولي للاعلام والدراسات           179     193.0   \n",
       "4                                        قولاً واحداً           297      19.0   \n",
       "...                                               ...           ...       ...   \n",
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       "40898                 رئاسة الجمهورية العربية السورية          1232     599.0   \n",
       "\n",
       "                                            contentclean  \n",
       "0                     امطار خفيفه تهطل العاصمه دمشق عدسه  \n",
       "1      قاعدين بلا شغل نقبض رواتب 🙂 احلى 🙃 اللاذقيه لل...  \n",
       "2      رادار البروق زخات مطر مصحوبه بالبروق بدات قليل...  \n",
       "3      الشارع يتالم لكنه تائه تحديد الخيارات عندما يت...  \n",
       "4                                    طريقي 📖📝🎓 قريبا جدا  \n",
       "...                                                  ...  \n",
       "40894  وحدات الهندسه الجيش العربي السوري تواصل مهامها...  \n",
       "40895  السيد الرئيس الفريق بشار الاسد يصدر المرسوم ال...  \n",
       "40896  يارب بحق اذان فجر يام شهر شعبان اللهم اجعل الا...  \n",
       "40897  ⭕ رئيس مجلس الشعب يعلن تبلغ المجلس قبل المحكمه...  \n",
       "40898  السيد الرئيس الفريق بشار الاسد القائد العام لل...  \n",
       "\n",
       "[40899 rows x 33 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('./Data/final_data_for_training.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "def split_data(data,y_cols,test_size=0.2,drops=[]):    \n",
    "    X = data.loc[:,~data.columns.isin(y_cols+drops)]\n",
    "    y = data.loc[:,y_cols]\n",
    "    X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=test_size,random_state=42)\n",
    "    return X_train, X_test,y_train,y_test\n",
    "\n",
    "def split_data_copy(data,y_cols,test_size=0.2,drops=[]):    \n",
    "    X = data.loc[:,~data.columns.isin(y_cols+drops)]\n",
    "    y = data.loc[:,y_cols]\n",
    "#     X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=test_size,random_state=42)\n",
    "    return X\n",
    "\n",
    "\n",
    "def clean_data(data, not_important_columns = [], normalize_reactions=False, min_row_per_page=100, min_posts_counts=100):\n",
    "    data = data[data.columns.difference(not_important_columns)].dropna()\n",
    "    # clean posts under number of posts:\n",
    "    data = data[data.sumreactions > min_posts_counts]\n",
    "    if normalize_reactions:\n",
    "        def normalization(item):\n",
    "            haha = item[\"haha\"]/item[\"sumreactions\"]\n",
    "            sad = item[\"sad\"]/item[\"sumreactions\"]\n",
    "            love= item[\"love\"]/item[\"sumreactions\"]\n",
    "            angry= item[\"angry\"]/item[\"sumreactions\"]\n",
    "            wow= item[\"wow\"]/item[\"sumreactions\"]\n",
    "            return haha, sad, love, angry, wow\n",
    "        data[['haha','sad','love','angry','wow']] = data.apply(normalization, axis=1, result_type=\"expand\")\n",
    "    \n",
    "    if \"page_name\" not in not_important_columns:\n",
    "        counts = data.page_name.value_counts() \n",
    "        counts = counts[counts > min_row_per_page]\n",
    "        counts_keys = list(counts.keys())\n",
    "        data = data[data.page_name.isin(counts_keys)]\n",
    "    return data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"prep\"></a>\n",
    "<h3><B><left>- Preprocessing:</left></B></h3>\n",
    "</I></h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "not_important_columns = [\"content\",\"contentclean\",\"page_name\",\"len_text\"]\n",
    "data = clean_data(df,not_important_columns,True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test,y_train,y_test = split_data(data,['haha','sad','love','angry','wow'],drops=['sumreactions'],test_size=0.8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import  OneHotEncoder,RobustScaler, StandardScaler, MinMaxScaler\n",
    "from sklearn.compose import make_column_transformer\n",
    "from sklearn.compose import make_column_selector\n",
    "\n",
    "\n",
    "ct = make_column_transformer(\n",
    "   (StandardScaler(),\n",
    "    make_column_selector(dtype_include=np.number)),\n",
    "   (OneHotEncoder(),\n",
    "    make_column_selector(dtype_include=object)))\n",
    "y_normalizer = MinMaxScaler(feature_range=(0,100))\n",
    "\n",
    "X_train = ct.fit_transform(X_train)\n",
    "X_test = ct.transform(X_test)\n",
    "\n",
    "y_train_t = y_train\n",
    "# y_normalizer.fit_transform(y_train)\n",
    "y_test_t = y_test\n",
    "# y_normalizer.transform(y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"model\"></a>\n",
    "<h3><B><left>- Modeling:</left></B></h3>\n",
    "</I></h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor\n",
    "from sklearn.linear_model import SGDClassifier,LinearRegression,Ridge\n",
    "model_pipline = Pipeline([\n",
    " ('classifier',RandomForestRegressor(n_estimators=9,min_samples_leaf=100))\n",
    " ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pipeline(steps=[('classifier',\n",
       "                 RandomForestRegressor(min_samples_leaf=100, n_estimators=9))])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_pipline.fit(X_train ,y_train_t)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"results\"></a>\n",
    "<h3><B><left>- Results:</left></B></h3>\n",
    "<a id=\"mse\"></a>\n",
    "<h4><I><left>- compute Mean Squared Error on all classes.</left></I></h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE Train: [0.03405639 0.01883734 0.03756915 0.00983142 0.00645736]\n",
      "MSE Test: [0.035924   0.01918413 0.03855131 0.01039039 0.00664676]\n",
      "\n",
      "Train Error 0.021, Test Error0.022\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "test_predicted = model_pipline.get_params()['classifier'].predict(X_test)\n",
    "train_predicted = model_pipline.get_params()['classifier'].predict(X_train)\n",
    "\n",
    "\n",
    "\n",
    "# compute MSE for every class:\n",
    "mse_test = mean_squared_error(y_test_t,test_predicted,multioutput='raw_values')\n",
    "mse_train = mean_squared_error(y_train_t,train_predicted,multioutput='raw_values')\n",
    "print(\"MSE Train: {:}\\nMSE Test: {:}\\n\".format(mse_train,mse_test))\n",
    "\n",
    "\n",
    "# mean of 3 result values:\n",
    "print('Train Error {:.3f}, Test Error{:.3f}'.format(np.mean(mse_train),np.mean(mse_test))) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"plot\"></a>\n",
    "<h4><I><left>- plot MSE using pyplot.</left></I></h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2878df4b4c8>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as pl\n",
    "\n",
    "pl.figure(figsize=(20,10))\n",
    "pl.plot(test_predicted[:100,1])\n",
    "# pl.plot(test_predicted[:1000,2])\n",
    "pl.plot(y_test['sad'].values[:100])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.70525896, 0.03175612, 0.11402822, 0.08483636, 0.06412033],\n",
       "       [0.01532431, 0.84140738, 0.03159939, 0.03472488, 0.07694403],\n",
       "       [0.7091473 , 0.04030401, 0.17845385, 0.03340376, 0.03869108],\n",
       "       ...,\n",
       "       [0.298297  , 0.17248237, 0.35326742, 0.08709447, 0.08885874],\n",
       "       [0.04547735, 0.69892321, 0.05296869, 0.07051914, 0.13211162],\n",
       "       [0.00675401, 0.00897333, 0.9772479 , 0.00108861, 0.00593615]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_predicted"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"export\"></a>\n",
    "<h3><B><left>- Exporting Model:</left></B></h3>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"save\"></a>\n",
    "<h4><I><left>- save into pickle</left></I></h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "with open('reactions_transformer_without_page_v28.8.pkl','wb') as file:\n",
    "    pickle.dump(ct,file)\n",
    "    \n",
    "import pickle\n",
    "with open('reactions_model_without_page_v28.8.pkl','wb') as file:\n",
    "    pickle.dump(model_pipline.get_params()['classifier'],file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"test\"></a>\n",
    "<h4><I><left>- test final models</left></I></h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "with open('reactions_transformer_with_page.pkl','rb') as file:\n",
    "    ct_with_page = pickle.load(file)\n",
    "    \n",
    "with open('reactions_model_with_page.pkl','rb') as file:\n",
    "    model = pickle.load(file)\n",
    "\n",
    "with open('reactions_transformer_without_page.pkl', 'rb') as file:\n",
    "    ct_without_page = pickle.load(file)\n",
    "with open('reactions_model_without_page.pkl', 'rb') as file:\n",
    "    model_without_page = pickle.load(file)\n",
    "\n",
    "def predict_reactions_with_page(features_set, pages_name):  \n",
    "    # service start:\n",
    "    ss = pd.Series()\n",
    "    df = pd.DataFrame()\n",
    "    for index, feature_vector in enumerate(features_set):\n",
    "        for i,feature in enumerate(feature_vector):\n",
    "            ss[str(i)] = feature\n",
    "        ss[\"page_name\"] = pages_name[index]\n",
    "    \n",
    "        df = df.append(ss,ignore_index=True)\n",
    "    \n",
    "    global ct_with_page\n",
    "    features_vector = ct_with_page.transform(df)\n",
    "    predicted = model.predict(features_vector)\n",
    "    return predicted\n",
    "\n",
    "def predict_reactions_without_page(features_set):  \n",
    "    # service start:\n",
    "    ss = pd.Series()\n",
    "    df = pd.DataFrame()\n",
    "    for feature_vector in features_set:\n",
    "        for i,feature in enumerate(feature_vector):\n",
    "            ss[str(i)] = feature\n",
    "        df = df.append(ss,ignore_index=True)\n",
    "    \n",
    "    global ct_without_page\n",
    "    features_vector = ct_without_page.transform(df)\n",
    "    predicted = model_without_page.predict(features_vector)\n",
    "    return predicted  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "df1 = pd.DataFrame(df.loc[0][['0','1','2','3','4','5','6','7','8','9','10','11','12','13','14','15','16','17','18','19','20','21','22']]).T\n",
    "df1['page_name'] = \"يوميات قذيفة هاون في دمشق\"\n",
    "# predicted = model_without_page.predict(featues_vector)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# the model input is features vector come from nlp_models(LSTM and BiLstm)\n",
    "features = [[ 0.0402259603142738, 0.0165141001343727, 0.9114372730255128,\n",
    "       -0.001352300401777, 0.0205039270222187, 0.0206228233873844,\n",
    "       0.0621627271175384, 0.0027457359246909, 0.0124617367982864,\n",
    "       0.9008947014808656, 0.0011122716823592, 0.0084417325306716,\n",
    "       0.0141683239889381, 0.0157450196891567, 0.0068691600280704,\n",
    "       0.0080397378568977, 0.007087407246732, 0.0222813333901275,\n",
    "       0.0083919570374671, 0.0068260526899215, 0.09132621337299,\n",
    "       0.4444434562865417, 0.366379591505193 ]]\n",
    "page_name = [\"يوميات قذيفة هاون في دمشق\"]\n",
    "\n",
    "# predict_reactions_with_page(features,page_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E:\\Applications\\Anaconda\\lib\\site-packages\\ipykernel_launcher.py:32: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.\n",
      "E:\\Applications\\Anaconda\\lib\\site-packages\\sklearn\\compose\\_column_transformer.py:440: FutureWarning: Given feature/column names or counts do not match the ones for the data given during fit. This will fail from v0.24.\n",
      "  FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 24.09558803,  12.81954896, 294.97662565,   2.54176715,\n",
       "          6.94266321]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predict_reactions_without_page(features)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3><I><center> ...The End...</center></I></h3>"
   ]
  }
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