{"metadata":{"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":4805127,"sourceType":"datasetVersion","datasetId":2782228}],"dockerImageVersionId":30746,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false},"colab":{"provenance":[{"file_id":"https://storage.googleapis.com/kaggle-colab-exported-notebooks/depression-and-anxiety-sentiment-6218f30a-4f71-4105-809c-f7681832c414.ipynb?X-Goog-Algorithm=GOOG4-RSA-SHA256&X-Goog-Credential=gcp-kaggle-com%40kaggle-161607.iam.gserviceaccount.com/20240712/auto/storage/goog4_request&X-Goog-Date=20240712T111929Z&X-Goog-Expires=259200&X-Goog-SignedHeaders=host&X-Goog-Signature=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","timestamp":1720783472367}],"gpuType":"T4"},"accelerator":"GPU"},"nbformat_minor":0,"nbformat":4,"cells":[{"cell_type":"markdown","source":["# About Dataset\n","The Mental Health Corpus is a collection of texts related to people with anxiety, depression, and other mental health issues. The corpus consists of two columns: one containing the comments, and the other containing labels indicating whether the comments are considered poisonous or not. The corpus can be used for a variety of purposes, such as sentiment analysis, toxic language detection, and mental health language analysis. The data in the corpus may be useful for researchers, mental health professionals, and others interested in understanding the language and sentiment surrounding mental health issues.\n","\n","text: the comments  \n","labels: 1 means considered as a comment which is poisonous with mental health issues, and 0 means not considered.\n"],"metadata":{"id":"WNUn0znmq2yu"}},{"cell_type":"code","source":["# Importing necessary libraries\n","import pandas as pd             # For data manipulation and analysis\n","import numpy as np              # For numerical operations\n","from scipy import stats         # For statistical computations\n","\n","import matplotlib.pyplot as plt # For plotting graphs\n","import seaborn as sns           # For data visualization\n","\n","# Importing necessary libraries for model evaluation and training-test split.\n","from sklearn.model_selection import train_test_split\n","from sklearn.linear_model import LogisticRegression\n","from sklearn.metrics import classification_report, accuracy_score, precision_score, recall_score, f1_score, roc_auc_score, confusion_matrix, ConfusionMatrixDisplay\n","\n","# Importing GridSearchCV from sklearn.model_selection for hyperparameter tuning.\n","from sklearn.model_selection import GridSearchCV\n","\n","# Importing XGBClassifier and plot_importance from xgboost for gradient boosting.\n","from xgboost import XGBClassifier, plot_importance\n","\n","# Import packages for data preprocessing\n","from sklearn.feature_extraction.text import CountVectorizer\n","\n","from xgboost import DMatrix"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T09:15:59.501831Z","iopub.execute_input":"2024-07-12T09:15:59.502615Z","iopub.status.idle":"2024-07-12T09:16:00.840344Z","shell.execute_reply.started":"2024-07-12T09:15:59.502553Z","shell.execute_reply":"2024-07-12T09:16:00.838996Z"},"trusted":true,"id":"TazsVKJQq2yv","executionInfo":{"status":"ok","timestamp":1720793859819,"user_tz":-180,"elapsed":693,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":64,"outputs":[]},{"cell_type":"code","source":["import torch"],"metadata":{"id":"li2zs2h0yehB","executionInfo":{"status":"ok","timestamp":1720793777226,"user_tz":-180,"elapsed":1,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":41,"outputs":[]},{"cell_type":"code","source":["print(torch.__version__)\n","print(torch.cuda.is_available())"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"nbA9Y4q-ygG8","executionInfo":{"status":"ok","timestamp":1720793778183,"user_tz":-180,"elapsed":3,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}},"outputId":"1bd0df76-ae0e-4cea-830a-d88dbce155da"},"execution_count":42,"outputs":[{"output_type":"stream","name":"stdout","text":["2.3.0+cu121\n","True\n"]}]},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"x31bnplJs_Jc","executionInfo":{"status":"ok","timestamp":1720793781513,"user_tz":-180,"elapsed":3332,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}},"outputId":"451e4e45-029c-4a9a-e465-c774116755cb"},"execution_count":43,"outputs":[{"output_type":"stream","name":"stdout","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"]}]},{"cell_type":"code","source":["df0 = pd.read_csv(\"/content/drive/MyDrive/Projects/depression-and-anxiety-sentiment/mental_health.csv\")"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T09:16:03.658157Z","iopub.execute_input":"2024-07-12T09:16:03.658577Z","iopub.status.idle":"2024-07-12T09:16:03.889865Z","shell.execute_reply.started":"2024-07-12T09:16:03.658547Z","shell.execute_reply":"2024-07-12T09:16:03.888381Z"},"trusted":true,"id":"u_o0Spk_q2yw","executionInfo":{"status":"ok","timestamp":1720793781513,"user_tz":-180,"elapsed":4,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":44,"outputs":[]},{"cell_type":"code","source":["df0.head()"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T09:16:04.753062Z","iopub.execute_input":"2024-07-12T09:16:04.753833Z","iopub.status.idle":"2024-07-12T09:16:04.770811Z","shell.execute_reply.started":"2024-07-12T09:16:04.753795Z","shell.execute_reply":"2024-07-12T09:16:04.769314Z"},"trusted":true,"id":"p_lHuZUzq2yw","outputId":"e81bcebc-cebe-464b-f2a1-c6ae6ccb361e","colab":{"base_uri":"https://localhost:8080/","height":206},"executionInfo":{"status":"ok","timestamp":1720793781513,"user_tz":-180,"elapsed":4,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":45,"outputs":[{"output_type":"execute_result","data":{"text/plain":["                                                text  label\n","0  dear american teens question dutch person hear...      0\n","1  nothing look forward lifei dont many reasons k...      1\n","2  music 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students teachers put medication rd grade everyday pulled classroom sit principal office would come home crying everyday mistreatment mom finally enough pulled public school transferred private christian school behind education next year retake rd grade students bullied started fight back aggressively also landed principals office th grade transferred back public school made friends bullies bad kids class want bullied anymore tough guy got girlfriend short lived ended writing notes wanted fuck bunch sexual stuff soon found grandma called principal school tried press charges minor gone puberty yet really understand ramifications saying grip parents tightened medication forced throat th grade teacher slapped across face class shut class still remember bead sweat rolling mustache red angry face slapped me made turn back hardened asshole teachers care school point wanted run away several times could never make friends felt like big fucking joke me fist fights recess involved somebody else typically started kids corned back fence friends said fuck friends need them th grade proceeded get girlfriend become sexually active th grade high school began relationship started take turn eventually ended longest friendship entire life devastating ended began get suicidal depression tried overdose medication class caught red handed taking entire bottle pills became violently ill blacked bathroom found carried nurses office school principal called ambulance contacted mom mom devastated pissed crying uncontrollably lied said accident switched meds antidepressants later stopped taking gag reflex overdose went  long term relationship breakups ended cutting arms burning lighter pulled class senior year high school arrested front whole school shooting front school paintball gun night before prank someone would clean charged  different things including terrorism absolutely drive become anything life think going live past  academically barely graduated high school convinced pull shit together go college failed college blew grant money food diamonds girlfriend relationship ended joined marine corps go die country iraq opf fallujah ex girlfriend came see california led wanted get back knew knew company getting deployed iraq fight real full metal jacket mental breakdown weeks deployed threatened kill bunch people landed hospital diagnosis ptsd bipolar major depression fraudulent enlistment charge given discharge honorable conditions plane ticket home tried go back school failed racked another bill year discharge girlfriend broke up friends considered failure everything let love life walk away soon keep depression control jumped relationship first girl would talk gas station convinced looks everything chick nice funny showed attention wanted cock cake care fucked head son already whose father jail decided would pull shit together roll model later started self medicating weed really cop felt great high time friends wifes friends supplying me temper really chilled smoked manic didnt filled uncontrollable anxietydepression rage often super asshole little man syndrome didnt smoke often thought redflag option stop internal pain instead saying loud would impulsively things hurt myself punched structure point shattered wrist several fingers felt better little bit marriage ended year later point interest forming new relationships anyone tired looking new connects weed moved around different states legal dispensaries soon realized weed helping actually making things worse control anymore desperate plea help sister gave place stay moving sister family found work started busting ass make things work could get place entire focus work smoking weed numb pain living often would isolate away everyone else could smoke weed cigarettes really acceptable lifestyle eventually led renting room house full strangers closer work work roommates knowing weed would go room steal weed play instruments work put huge panic major anxiety depression eventually leave situation move back sister brother law take well year started throwing offensive false accusations sexually since interested dating divorce nephews would repeat said friends friends parents soon everyone treated fucked way made things even worse instead giving getting defensive fucking talking shit decided pack shit leave found cheap place live way woods away everyone else keep myself working employer  years started feel little comfortable around coworkers opened little relate mentioned high school paintballing incident normal conversation conflicts employer soon started take place coworker told boss paintballing played sociopath wanted job pay concerned thought boss knew well enough believe later sit boss talk future goals told goal make better future plans start business real grown shit like one bit fact retaliated cutting hours bonus pay singled rest crew made work jobs less time complete pressure unbearable redflag plate everyday every hour constantly mind started feel ill overwhelming uncontrollable feelings panic attack quit job health insurance afford cost housing car payments insurance cellphone bill ended going doctor heart would beat chest throwing every morning years wanted know why turns heart enlarged may diabetes stage  hypertension might heart attack stroke cant relieve stress take care myself got way refused take medications instead still self medicating stop weed without losing mind emotionally stopped smoking weedcigs mt dew per doctors request save life anxiety debilitating obsess death cant hold conversation cant share eye contact feel extremely uncomfortable every social situation encounter cant bring back normal feel like normal wanting kill ending existence im running short money bank feel like work people fucking minion worker slave would rather die life completely closed feel though time running out well self control hide painful memories mom traveled  miles past slipped said going kill extremely worried depressed feels like lose child even tho ive said nothing recently actually moved woods far away everyone kill myself nobody would find me cant sleep anymore mind always thinking ways go every tree look at see hanging every gun looks see blood scattered wall body slumped over every tall building see body bouncing pavement every light pole see think truck wrapped around body half way hood windshield go jog try clear mind feel urge step front car semi head hurts cant help punch face burn propane torch relieve pain extremely difficult time analyzing events life absolutely hating people theyve done me hating unable forgive forget move on shitty things ive said done people control myself thought redflag might parents kept here feel hard even around family hour without irritated rude hate everything me starting understand everyone else hates too hurtful things go away cannot help desperately want become ash float away space dot planet insignificant every way mankind nothing offer feel ashamed illness feel like waste space oxygen pray god blow heart chest mom dad would live fact son willingly killed himself\",\n          \"wanna use omegle cus self esteems low ppl always compliment saw ppl saying got doxxed using omegle shit uhh meh oh well\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"label\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  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X_train_temp, X_test, y_train_temp, y_test = train_test_split(X, y, test_size=0.20, stratify=y, random_state=65537)\n","    X_train, X_val, y_train, y_val = train_test_split(X_train_temp, y_train_temp, test_size=0.25, stratify=y_train_temp, random_state=65537)\n","    return X_train, X_test, X_val, y_train, y_test, y_val, X, y\n"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T09:16:13.41506Z","iopub.execute_input":"2024-07-12T09:16:13.415963Z","iopub.status.idle":"2024-07-12T09:16:13.423401Z","shell.execute_reply.started":"2024-07-12T09:16:13.415923Z","shell.execute_reply":"2024-07-12T09:16:13.421966Z"},"trusted":true,"id":"nVH_qstlq2yy","executionInfo":{"status":"ok","timestamp":1720793782055,"user_tz":-180,"elapsed":3,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":51,"outputs":[]},{"cell_type":"code","source":["X_train, X_test, X_val, y_train, y_test, y_val, X, y = train_test_valid_split(df, target = \"label\")"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T09:16:14.821796Z","iopub.execute_input":"2024-07-12T09:16:14.822307Z","iopub.status.idle":"2024-07-12T09:16:14.863041Z","shell.execute_reply.started":"2024-07-12T09:16:14.822268Z","shell.execute_reply":"2024-07-12T09:16:14.861957Z"},"trusted":true,"id":"8Mc3uJFsq2yz","executionInfo":{"status":"ok","timestamp":1720793782055,"user_tz":-180,"elapsed":3,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":52,"outputs":[]},{"cell_type":"code","source":["dfs = [X_train, X_test, X_val, y_train, y_test, y_val]"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T09:16:15.31045Z","iopub.execute_input":"2024-07-12T09:16:15.31095Z","iopub.status.idle":"2024-07-12T09:16:15.317343Z","shell.execute_reply.started":"2024-07-12T09:16:15.310913Z","shell.execute_reply":"2024-07-12T09:16:15.315792Z"},"trusted":true,"id":"w3Jj9sDYq2yz","executionInfo":{"status":"ok","timestamp":1720793782425,"user_tz":-180,"elapsed":1,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":53,"outputs":[]},{"cell_type":"code","source":["for i in dfs:\n","    print(i.shape)"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T09:16:15.86964Z","iopub.execute_input":"2024-07-12T09:16:15.870465Z","iopub.status.idle":"2024-07-12T09:16:15.877242Z","shell.execute_reply.started":"2024-07-12T09:16:15.870425Z","shell.execute_reply":"2024-07-12T09:16:15.875949Z"},"trusted":true,"id":"rvAH9XN_q2yz","outputId":"ac748016-15a6-4703-988c-65a1659085f2","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1720793782827,"user_tz":-180,"elapsed":2,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":54,"outputs":[{"output_type":"stream","name":"stdout","text":["(16782, 1)\n","(5595, 1)\n","(5595, 1)\n","(16782,)\n","(5595,)\n","(5595,)\n"]}]},{"cell_type":"markdown","source":["# CountVectorizer"],"metadata":{"id":"cILQsCF9q2yz"}},{"cell_type":"code","source":["# Set up a `CountVectorizer` object, which converts a collection of text to a matrix of token counts\n","count_vec = CountVectorizer(ngram_range=(2, 4),\n","                            max_features=2000,\n","                            stop_words='english',\n","                            lowercase=True)\n","count_vec"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T10:34:07.840283Z","iopub.execute_input":"2024-07-12T10:34:07.840752Z","iopub.status.idle":"2024-07-12T10:34:07.851703Z","shell.execute_reply.started":"2024-07-12T10:34:07.840718Z","shell.execute_reply":"2024-07-12T10:34:07.850444Z"},"trusted":true,"id":"6IDchHcJq2yz","outputId":"5f1da514-180f-4400-d3c6-d8b34d0d782f","colab":{"base_uri":"https://localhost:8080/","height":75},"executionInfo":{"status":"ok","timestamp":1720793784326,"user_tz":-180,"elapsed":3,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":55,"outputs":[{"output_type":"execute_result","data":{"text/plain":["CountVectorizer(max_features=2000, ngram_range=(2, 4), stop_words='english')"],"text/html":["<style>#sk-container-id-3 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See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>CountVectorizer(max_features=2000, ngram_range=(2, 4), stop_words=&#x27;english&#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\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" checked><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">CountVectorizer</label><div class=\"sk-toggleable__content\"><pre>CountVectorizer(max_features=2000, ngram_range=(2, 4), stop_words=&#x27;english&#x27;)</pre></div></div></div></div></div>"]},"metadata":{},"execution_count":55}]},{"cell_type":"code","source":["%%time\n","# Wall time ~ 12.3 s\n","# Extract numerical features from `video_transcription_text` in the training set\n","count_data = count_vec.fit_transform(X_train[\"text\"]).toarray()\n","count_data"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T10:34:09.164687Z","iopub.execute_input":"2024-07-12T10:34:09.16516Z","iopub.status.idle":"2024-07-12T10:34:21.497421Z","shell.execute_reply.started":"2024-07-12T10:34:09.165125Z","shell.execute_reply":"2024-07-12T10:34:21.495853Z"},"trusted":true,"id":"YGIs-sW_q2yz","outputId":"ae2698f9-0e88-4f72-f451-a93d58b637c2","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1720793803980,"user_tz":-180,"elapsed":19656,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":56,"outputs":[{"output_type":"stream","name":"stdout","text":["CPU times: user 14.4 s, sys: 597 ms, total: 15 s\n","Wall time: 19.3 s\n"]},{"output_type":"execute_result","data":{"text/plain":["array([[0, 0, 0, ..., 0, 0, 0],\n","       [0, 0, 0, ..., 0, 0, 0],\n","       [0, 0, 0, ..., 0, 0, 0],\n","       ...,\n","       [0, 0, 0, ..., 0, 0, 0],\n","       [0, 0, 0, ..., 0, 0, 0],\n","       [0, 0, 0, ..., 0, 0, 0]])"]},"metadata":{},"execution_count":56}]},{"cell_type":"code","source":["# Place the numerical representation of `video_transcription_text` from training set into a dataframe\n","count_df = pd.DataFrame(data=count_data, columns=count_vec.get_feature_names_out())\n","\n","# Display first few rows\n","count_df.head()"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T10:34:41.466843Z","iopub.execute_input":"2024-07-12T10:34:41.467335Z","iopub.status.idle":"2024-07-12T10:34:41.498478Z","shell.execute_reply.started":"2024-07-12T10:34:41.467292Z","shell.execute_reply":"2024-07-12T10:34:41.497147Z"},"trusted":true,"id":"AnfEqjl8q2yz","outputId":"fb91bf61-45b6-4dab-d618-6368f9ca9f00","colab":{"base_uri":"https://localhost:8080/","height":253},"executionInfo":{"status":"ok","timestamp":1720793803980,"user_tz":-180,"elapsed":13,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":57,"outputs":[{"output_type":"execute_result","data":{"text/plain":["   able afford  able help  able live  able make  abusive relationship  \\\n","0            0          0          0          0                     0   \n","1            0          0          0          0                     0   \n","2            0          0          0          0                  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rows\n","X_train_final.head()"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T10:34:43.083824Z","iopub.execute_input":"2024-07-12T10:34:43.084929Z","iopub.status.idle":"2024-07-12T10:34:43.587677Z","shell.execute_reply.started":"2024-07-12T10:34:43.084839Z","shell.execute_reply":"2024-07-12T10:34:43.586161Z"},"trusted":true,"id":"HTe0GJH6q2yz","outputId":"08a7c425-64e1-4e9d-b671-72525be8b764","colab":{"base_uri":"https://localhost:8080/","height":253},"executionInfo":{"status":"ok","timestamp":1720793804482,"user_tz":-180,"elapsed":514,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":58,"outputs":[{"output_type":"execute_result","data":{"text/plain":["   able afford  able help  able live  able make  abusive relationship  \\\n","0            0          0          0          0                     0   \n","1            0          0          0          0                     0   \n","2            0          0          0          0            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axis=1)\n","X_test_final.head()"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T10:34:50.05302Z","iopub.execute_input":"2024-07-12T10:34:50.053464Z","iopub.status.idle":"2024-07-12T10:34:51.349165Z","shell.execute_reply.started":"2024-07-12T10:34:50.053432Z","shell.execute_reply":"2024-07-12T10:34:51.347386Z"},"trusted":true,"id":"WxsRyhSHq2y0","outputId":"1bb00264-2896-4ac3-a590-579eed97a40a","colab":{"base_uri":"https://localhost:8080/","height":253},"executionInfo":{"status":"ok","timestamp":1720793808477,"user_tz":-180,"elapsed":2043,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":62,"outputs":[{"output_type":"execute_result","data":{"text/plain":["   able afford  able help  able live  able make  abusive relationship  \\\n","0            0          0          0          0                     0   \n","1            0          0          0          0                     0   \n","2            0          0          0          0          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Serdar","userId":"12855363183913540285"}}},"execution_count":73,"outputs":[]},{"cell_type":"code","source":["# Defining the grid of parameters for XGBoost classifier tuning.\n","cv_params = {\n","    'max_depth': [4, 8, 12],\n","    'min_child_weight': [1, 2],\n","    'learning_rate': [0.2, 0.4, 0.6],\n","    'n_estimators': [50, 100, 200, 400]\n","}"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T10:34:56.403058Z","iopub.execute_input":"2024-07-12T10:34:56.40413Z","iopub.status.idle":"2024-07-12T10:34:56.410751Z","shell.execute_reply.started":"2024-07-12T10:34:56.404075Z","shell.execute_reply":"2024-07-12T10:34:56.408966Z"},"trusted":true,"id":"4gvc-5-Kq2y0","executionInfo":{"status":"ok","timestamp":1720794119654,"user_tz":-180,"elapsed":366,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":74,"outputs":[]},{"cell_type":"code","source":["# Defining the scoring metrics to be used in GridSearchCV for XGBoost classifier.\n","scoring = {'accuracy', 'precision', 'recall', 'f1', 'roc_auc'}"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T10:34:57.826208Z","iopub.execute_input":"2024-07-12T10:34:57.826652Z","iopub.status.idle":"2024-07-12T10:34:57.832381Z","shell.execute_reply.started":"2024-07-12T10:34:57.826619Z","shell.execute_reply":"2024-07-12T10:34:57.831072Z"},"trusted":true,"id":"ZaCqrTg7q2y0","executionInfo":{"status":"ok","timestamp":1720794121770,"user_tz":-180,"elapsed":410,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":75,"outputs":[]},{"cell_type":"code","source":["# Creating a GridSearchCV object xgb for XGBoost classifier tuning.\n","xgb = GridSearchCV(xgb_cls, cv_params, scoring=scoring, cv=5, refit='roc_auc')"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T10:34:59.862428Z","iopub.execute_input":"2024-07-12T10:34:59.862855Z","iopub.status.idle":"2024-07-12T10:34:59.869147Z","shell.execute_reply.started":"2024-07-12T10:34:59.862823Z","shell.execute_reply":"2024-07-12T10:34:59.867702Z"},"trusted":true,"id":"iNf_AB7iq2y0","executionInfo":{"status":"ok","timestamp":1720794123490,"user_tz":-180,"elapsed":456,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":76,"outputs":[]},{"cell_type":"code","source":["%%time\n","# Fit the model\n","# Wall time ~ 32min 59s\n","\n","xgb.fit(X_train_final, y_train)"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T10:35:01.590302Z","iopub.execute_input":"2024-07-12T10:35:01.5911Z","iopub.status.idle":"2024-07-12T11:13:43.043895Z","shell.execute_reply.started":"2024-07-12T10:35:01.591032Z","shell.execute_reply":"2024-07-12T11:13:43.041685Z"},"trusted":true,"id":"PDqxlTPJq2y0","outputId":"2f09e5ac-ec65-4de9-fa7d-0bd7966cb3c7","colab":{"base_uri":"https://localhost:8080/","height":391},"executionInfo":{"status":"ok","timestamp":1720794353648,"user_tz":-180,"elapsed":353,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":80,"outputs":[{"output_type":"error","ename":"TypeError","evalue":"Singleton array array(<xgboost.core.DMatrix object at 0x79f49c7f1c30>, dtype=object) cannot be considered a valid collection.","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)","\u001b[0;32m<timed eval>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/sklearn/model_selection/_search.py\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y, groups, **fit_params)\u001b[0m\n\u001b[1;32m    780\u001b[0m             \u001b[0mrefit_metric\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrefit\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    781\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 782\u001b[0;31m         \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgroups\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mindexable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgroups\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    783\u001b[0m         \u001b[0mfit_params\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_check_fit_params\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfit_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    784\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mindexable\u001b[0;34m(*iterables)\u001b[0m\n\u001b[1;32m    441\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    442\u001b[0m     \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0m_make_indexable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mX\u001b[0m \u001b[0;32min\u001b[0m \u001b[0miterables\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 443\u001b[0;31m     \u001b[0mcheck_consistent_length\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    444\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    445\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_consistent_length\u001b[0;34m(*arrays)\u001b[0m\n\u001b[1;32m    392\u001b[0m     \"\"\"\n\u001b[1;32m    393\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 394\u001b[0;31m     \u001b[0mlengths\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0m_num_samples\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mX\u001b[0m \u001b[0;32min\u001b[0m \u001b[0marrays\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mX\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    395\u001b[0m     \u001b[0muniques\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlengths\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    396\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muniques\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    392\u001b[0m     \"\"\"\n\u001b[1;32m    393\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 394\u001b[0;31m     \u001b[0mlengths\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0m_num_samples\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mX\u001b[0m \u001b[0;32min\u001b[0m \u001b[0marrays\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mX\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    395\u001b[0m     \u001b[0muniques\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlengths\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    396\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muniques\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36m_num_samples\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m    333\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"shape\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    334\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 335\u001b[0;31m             raise TypeError(\n\u001b[0m\u001b[1;32m    336\u001b[0m                 \u001b[0;34m\"Singleton array %r cannot be considered a valid collection.\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    337\u001b[0m             )\n","\u001b[0;31mTypeError\u001b[0m: Singleton array array(<xgboost.core.DMatrix object at 0x79f49c7f1c30>, dtype=object) cannot be considered a valid collection."]}]},{"cell_type":"code","source":["import os\n","import pickle\n","\n","def write_pickle(path, model_object, save_as:str):\n","    '''\n","    In:\n","        path:         path of folder where you want to save the pickle\n","        model_object: a model you want to pickle\n","        save_as:      filename for how you want to save the model\n","\n","    Out: A call to pickle the model in the folder indicated\n","    '''\n","    if not os.path.exists(path):\n","        os.makedirs(path)\n","    with open(path + save_as + '.pickle', 'wb') as to_write:\n","        pickle.dump(model_object, to_write)\n","\n","def read_pickle(path, saved_model_name:str):\n","    '''\n","    In:\n","        path:             path to folder where you want to read from\n","        saved_model_name: filename of pickled model you want to read in\n","\n","    Out:\n","        model: the pickled model\n","    '''\n","    with open(path + saved_model_name + '.pickle', 'rb') as to_read:\n","        model = pickle.load(to_read)\n","\n","    return model"],"metadata":{"id":"k9qedxGVG8kA","executionInfo":{"status":"ok","timestamp":1720790564635,"user_tz":-180,"elapsed":351,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":29,"outputs":[]},{"cell_type":"code","source":["path = \"/content/drive/MyDrive/Projects/depression-and-anxiety-sentiment/model_objects/\""],"metadata":{"id":"S2U-20bCHFgr","executionInfo":{"status":"ok","timestamp":1720790641478,"user_tz":-180,"elapsed":318,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":30,"outputs":[]},{"cell_type":"code","source":["# To write\n","write_pickle(path, xgb, 'xgb')"],"metadata":{"id":"LyPdnyXOHQHp","executionInfo":{"status":"ok","timestamp":1720790643465,"user_tz":-180,"elapsed":312,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":31,"outputs":[]},{"cell_type":"code","source":["# To read\n","xgb = read_pickle(path, 'xgb')"],"metadata":{"id":"rbDzGkHYHRZ3","executionInfo":{"status":"ok","timestamp":1720794537639,"user_tz":-180,"elapsed":365,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":81,"outputs":[]},{"cell_type":"code","source":["xgb.best_score_, xgb.best_params_"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T11:18:14.65614Z","iopub.execute_input":"2024-07-12T11:18:14.656663Z","iopub.status.idle":"2024-07-12T11:18:14.668716Z","shell.execute_reply.started":"2024-07-12T11:18:14.656628Z","shell.execute_reply":"2024-07-12T11:18:14.667118Z"},"trusted":true,"id":"95N7BAGUq2y1","outputId":"8ac42525-a138-4dd7-e057-3b94a84b97ec","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1720794540299,"user_tz":-180,"elapsed":368,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":82,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(0.8972465235303669,\n"," {'learning_rate': 0.2,\n","  'max_depth': 12,\n","  'min_child_weight': 1,\n","  'n_estimators': 400})"]},"metadata":{},"execution_count":82}]},{"cell_type":"code","source":["y_val_pred = xgb.best_estimator_.predict(X_val_final)"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T11:18:17.475388Z","iopub.execute_input":"2024-07-12T11:18:17.475854Z","iopub.status.idle":"2024-07-12T11:18:17.959389Z","shell.execute_reply.started":"2024-07-12T11:18:17.475816Z","shell.execute_reply":"2024-07-12T11:18:17.958288Z"},"trusted":true,"id":"R78mHnjTq2y1","executionInfo":{"status":"ok","timestamp":1720794543625,"user_tz":-180,"elapsed":876,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":83,"outputs":[]},{"cell_type":"code","source":["# Compute values for confusion matrix\n","log_cm = confusion_matrix(y_val, y_val_pred)\n","\n","# Create display of confusion matrix\n","log_disp = ConfusionMatrixDisplay(confusion_matrix=log_cm, display_labels=None)\n","\n","# Plot confusion matrix\n","log_disp.plot()\n","\n","# Display plot\n","plt.title('XGBoost - validation set');\n","plt.show()\n"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T11:18:20.509146Z","iopub.execute_input":"2024-07-12T11:18:20.510771Z","iopub.status.idle":"2024-07-12T11:18:20.923582Z","shell.execute_reply.started":"2024-07-12T11:18:20.510724Z","shell.execute_reply":"2024-07-12T11:18:20.922283Z"},"trusted":true,"id":"jO5UgqHUq2y1","outputId":"1deca505-f660-47fd-9cad-1f1ecaf44baf","colab":{"base_uri":"https://localhost:8080/","height":472},"executionInfo":{"status":"ok","timestamp":1720794546313,"user_tz":-180,"elapsed":908,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":84,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["# Create a classification report\n","target_labels = [\"not poisonous\", \"poisonous\"]\n","print(classification_report(y_val, y_val_pred, target_names=target_labels))\n","\n","# Compute and print ROC-AUC score\n","roc_auc = roc_auc_score(y_val, y_val_pred)  # Adjust y_pred based on your predictions\n","print(f\"ROC-AUC Score: {roc_auc:.4f}\")"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T11:18:24.068248Z","iopub.execute_input":"2024-07-12T11:18:24.06871Z","iopub.status.idle":"2024-07-12T11:18:24.100517Z","shell.execute_reply.started":"2024-07-12T11:18:24.068675Z","shell.execute_reply":"2024-07-12T11:18:24.099336Z"},"trusted":true,"id":"VdT7m-emq2y1","outputId":"ce5a8781-ef42-4f84-e9c5-d8c757724538","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1720794549326,"user_tz":-180,"elapsed":415,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":85,"outputs":[{"output_type":"stream","name":"stdout","text":["               precision    recall  f1-score   support\n","\n","not poisonous       0.80      0.91      0.85      2827\n","    poisonous       0.89      0.76      0.82      2768\n","\n","     accuracy                           0.84      5595\n","    macro avg       0.85      0.84      0.84      5595\n"," weighted avg       0.85      0.84      0.84      5595\n","\n","ROC-AUC Score: 0.8377\n"]}]},{"cell_type":"markdown","source":["Weight: Shows how many times each feature is used to split the data across all trees.  \n","Gain: Measures the improvement in accuracy brought by a feature to the branches it is on.  \n","Cover: Indicates the relative quantity of observations concerned by a feature."],"metadata":{"id":"TTb59tIyq2y1"}},{"cell_type":"code","source":["import matplotlib.pyplot as plt\n","from xgboost import plot_importance\n","\n","fig, ax = plt.subplots(3, 1, figsize=(6, 24))\n","\n","# Weight\n","plot_importance(xgb.best_estimator_, importance_type='weight', ax=ax[0], title='Feature Importance (Weight)', max_num_features=15, values_format = \"{v:.2f}\")\n","\n","# Gain\n","plot_importance(xgb.best_estimator_, importance_type='gain', ax=ax[1], title='Feature Importance (Gain)', max_num_features=15, values_format = \"{v:.2f}\")\n","\n","# Cover\n","plot_importance(xgb.best_estimator_, importance_type='cover', ax=ax[2], title='Feature Importance (Cover)', max_num_features=15, values_format = \"{v:.2f}\")\n","\n","plt.show()\n"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T11:18:27.74367Z","iopub.execute_input":"2024-07-12T11:18:27.744151Z","iopub.status.idle":"2024-07-12T11:18:34.50953Z","shell.execute_reply.started":"2024-07-12T11:18:27.744112Z","shell.execute_reply":"2024-07-12T11:18:34.508164Z"},"trusted":true,"id":"I-FERTQ9q2y1","outputId":"4e4c6f11-b0f4-4ba7-fd32-1bff62e67f1e","colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"status":"ok","timestamp":1720794553950,"user_tz":-180,"elapsed":1684,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":86,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 600x2400 with 3 Axes>"],"image/png":"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Initialize the model_scores DataFrame\n","model_scores = pd.DataFrame(columns=[\"Model\", \"Precision\", \"Recall\", \"Accuracy\", \"F1\", \"roc_auc\"])\n","\n","def get_scores(model_name, y_test, y_pred, model_scores):\n","    \"\"\"\n","    Compute evaluation metrics and append to model_scores DataFrame.\n","\n","    Parameters:\n","    - model_name: Name of the model.\n","    - y_test: True labels.\n","    - y_pred: Predicted labels from the model.\n","    - model_scores: DataFrame to append scores.\n","\n","    Returns:\n","    - Updated model_scores DataFrame.\n","    \"\"\"\n","    precision = precision_score(y_test, y_pred)\n","    recall = recall_score(y_test, y_pred)\n","    accuracy = accuracy_score(y_test, y_pred)\n","    f1 = f1_score(y_test, y_pred)\n","    roc_auc = roc_auc_score(y_test, y_pred)\n","\n","    # Create DataFrame with scores for the current model\n","    scores_df = pd.DataFrame([[model_name, precision, recall, accuracy, f1, roc_auc]],\n","                             columns=[\"Model\", \"Precision\", \"Recall\", \"Accuracy\", \"F1\", \"roc_auc\"])\n","\n","    # Append scores to model_scores DataFrame\n","    model_scores = pd.concat([model_scores, scores_df], ignore_index=True)\n","\n","    return model_scores"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T11:18:58.806549Z","iopub.execute_input":"2024-07-12T11:18:58.807023Z","iopub.status.idle":"2024-07-12T11:18:58.820547Z","shell.execute_reply.started":"2024-07-12T11:18:58.806985Z","shell.execute_reply":"2024-07-12T11:18:58.819191Z"},"trusted":true,"id":"-k7MlCorq2y2","executionInfo":{"status":"ok","timestamp":1720794573917,"user_tz":-180,"elapsed":356,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":87,"outputs":[]},{"cell_type":"code","source":["# Update the model_scores DataFrame\n","model_scores = get_scores(model_name = \"CountVectorizer XGB val\", y_test = y_val, y_pred= y_val_pred, model_scores = model_scores)"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T11:19:00.755518Z","iopub.execute_input":"2024-07-12T11:19:00.756006Z","iopub.status.idle":"2024-07-12T11:19:00.785174Z","shell.execute_reply.started":"2024-07-12T11:19:00.755969Z","shell.execute_reply":"2024-07-12T11:19:00.783814Z"},"trusted":true,"id":"E-1VOw08q2y2","executionInfo":{"status":"ok","timestamp":1720794578295,"user_tz":-180,"elapsed":352,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":88,"outputs":[]},{"cell_type":"code","source":["model_scores"],"metadata":{"execution":{"iopub.status.busy":"2024-07-12T11:19:02.212082Z","iopub.execute_input":"2024-07-12T11:19:02.212558Z","iopub.status.idle":"2024-07-12T11:19:02.228858Z","shell.execute_reply.started":"2024-07-12T11:19:02.212524Z","shell.execute_reply":"2024-07-12T11:19:02.227426Z"},"trusted":true,"id":"zOhK0oKiq2y2","outputId":"67a2158d-e907-409d-bd05-b4e4195ef401","colab":{"base_uri":"https://localhost:8080/","height":89},"executionInfo":{"status":"ok","timestamp":1720794580856,"user_tz":-180,"elapsed":420,"user":{"displayName":"Can Serdar","userId":"12855363183913540285"}}},"execution_count":89,"outputs":[{"output_type":"execute_result","data":{"text/plain":["                     Model  Precision    Recall  Accuracy        F1   roc_auc\n","0  CountVectorizer XGB val   0.893249  0.764812  0.838427  0.824056  0.837659"],"text/html":["\n","  <div 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