{"id":146621,"date":"2025-08-18T12:00:42","date_gmt":"2025-08-18T06:30:42","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=146621"},"modified":"2025-08-18T12:00:42","modified_gmt":"2025-08-18T06:30:42","slug":"loan-approval-classifier-using-machine-learning","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/loan-approval-classifier-using-machine-learning\/","title":{"rendered":"ML Project &#8211; Loan Approval Classifier using Random Forest"},"content":{"rendered":"<h3>Program 1<\/h3>\n<p><a href=\"https:\/\/drive.google.com\/file\/d\/1TMtSutfHSHy7H3U70LLXAE1Icrc7OdDg\/view?usp=sharing\"><strong>Loan Dataset<\/strong><\/a><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\">Loan Approval Classifier using Random Forest\r\n\r\n\r\nimport pandas as pd\r\nfrom sklearn.model_selection import train_test_split\r\nfrom sklearn.preprocessing import LabelEncoder\r\nfrom sklearn.ensemble import RandomForestClassifier\r\nfrom sklearn.metrics import accuracy_score\r\n\r\ndf_loan=pd.read_csv(\"D:\/\/scikit_data\/loanData\/loan_data.csv\")\r\n\r\ndf_loan.head()\r\n\r\ndf_loan.shape\r\n\r\ndf_loan.info()\r\n\r\ndf_loan.isnull().sum()\r\n\r\n# Label Encoding\r\nle=LabelEncoder()\r\ndf_loan['Gender']=le.fit_transform(df_loan['Gender'])\r\ndf_loan['Married']=le.fit_transform(df_loan['Married'])\r\ndf_loan['Education']=le.fit_transform(df_loan['Education'])\r\ndf_loan['Loan_Status']=le.fit_transform(df_loan['Loan_Status'])\r\n\r\ndf_loan.info()\r\n\r\ndf_loan.head()\r\n\r\ndf_loan=df_loan.drop(['Unnamed: 6'],axis='columns')\r\n\r\ndf_loan\r\n\r\nX = df_loan.drop(\"Loan_Status\", axis=1) # Independed variables\r\ny = df_loan[\"Loan_Status\"] # Depended variables\r\n\r\nX\r\n\r\ny\r\n\r\n# Split data into train and test\r\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\r\n\r\nlen(X_train)\r\n\r\nlen(X_test)\r\n\r\n# Train Random Forest model\r\nmodel = RandomForestClassifier(n_estimators=100, random_state=42)\r\n\r\nmodel\r\n\r\nmodel.fit(X_train,y_train)\r\n\r\n# Make predictions\r\ny_pred = model.predict(X_test)\r\n\r\n# Evaluate\r\nprint(\"Accuracy:\", accuracy_score(y_test, y_pred))\r\n\r\ndf_loan\r\n\r\nmodel.predict([[1,1,0,5000,200]])\r\n\r\nmodel.predict([[0,0,1,3200,115]])\r\n\r\ngen=int(input(\"Enter Gender(Male-1 ,Female-0) :\"))\r\nmar=int(input(\"Enter Married Status (1-Yes 0-No) :\"))\r\nedu=int(input(\"Enter Your Education:(Graduate-0,Not Graduate 1) :\"))\r\ntc=int(input(\"Enter ApplicantIncome:\"))\r\namt=float(input(\"Enter LoanAmount :\"))\r\n\r\nresult=model.predict([[gen,mar,edu,tc,amt]])\r\nif(result==1):\r\n    print(\"********Loan Approved*******\")\r\nelse:\r\n    print(\".......Loan is Cancel .....\")\r\n<\/pre>\n<p>&nbsp;<span hidden class=\"__iawmlf-post-loop-links\" data-iawmlf-links=\"[{&quot;id&quot;:18,&quot;href&quot;:&quot;https:\\\/\\\/drive.google.com\\\/file\\\/d\\\/1TMtSutfHSHy7H3U70LLXAE1Icrc7OdDg\\\/view?usp=sharing&quot;,&quot;archived_href&quot;:&quot;http:\\\/\\\/web-wp.archive.org\\\/web\\\/20251205101720\\\/https:\\\/\\\/drive.google.com\\\/file\\\/d\\\/1TMtSutfHSHy7H3U70LLXAE1Icrc7OdDg\\\/view?usp=sharing&quot;,&quot;redirect_href&quot;:&quot;&quot;,&quot;checks&quot;:[{&quot;date&quot;:&quot;2025-12-19 03:25:33&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-01-12 10:48:44&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-01-25 23:11:49&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-03-13 08:56:08&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-04-29 10:50:10&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-12 10:39:39&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-06-22 11:26:19&quot;,&quot;http_code&quot;:200}],&quot;broken&quot;:false,&quot;last_checked&quot;:{&quot;date&quot;:&quot;2026-06-22 11:26:19&quot;,&quot;http_code&quot;:200},&quot;process&quot;:&quot;done&quot;}]\"><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Program 1 Loan Dataset Loan Approval Classifier using Random Forest import pandas as pd from sklearn.model_selection import train_test_split from sklearn.preprocessing import LabelEncoder from sklearn.ensemble import RandomForestClassifier from sklearn.metrics import accuracy_score df_loan=pd.read_csv(&#8220;D:\/\/scikit_data\/loanData\/loan_data.csv&#8221;) df_loan.head() df_loan.shape df_loan.info()&#46;&#46;&#46;<\/p>\n","protected":false},"author":581,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[36],"tags":[34766,35072,35071,8431,33127,33128,35073,20697],"class_list":["post-146621","post","type-post","status-publish","format-standard","hentry","category-machine-learning","tag-loan-approval-classifier","tag-loan-approval-classifier-using-machine-learning","tag-loan-approval-classifier-using-random-forest-algorithm","tag-machine-learning","tag-machine-learning-practical","tag-machine-learning-program","tag-machine-learning-program-on-loan-approval-classifier","tag-machine-learning-project"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>ML Project - Loan Approval Classifier using Random Forest - DataFlair<\/title>\n<meta name=\"robots\" content=\"index, follow, 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