College Dataset<\/strong><\/a><\/p>\n# To build a machine learning model that can predict the annual tuition fee of a\r\n# private college based on:\r\n# Its ranking , The student satisfaction score , The placement rate\r\nimport pandas as pd\r\nimport numpy as np\r\nfrom sklearn.linear_model import LinearRegression\r\n# Load Excel file\r\ndf = pd.read_excel(\"D:\/\/MLFile\/college_data.xlsx\")\r\n#print(df.isnull().sum())\r\n\r\n# Display top rows (optional)\r\n# print(\"Sample Data:\\n\", df.head())\r\n#\r\n# Define features and target i.e Independed and Depended variables\r\nX = df[['Ranking', 'Student_Satisfaction', 'Placement_Rate (%)']]\r\ny = df['Tuition_Fee ($)']\r\n#\r\n# # Train Linear Regression model\r\nmodel = LinearRegression()\r\nmodel.fit(X, y) # Independed and Depended variables\r\nprint(model)\r\n\r\n# Get user input\r\nranking = float(input(\"Enter College Ranking (1 = Best): \"))\r\nsatisfaction = float(input(\"Enter Student Satisfaction Score (0-10): \"))\r\nplacement = float(input(\"Enter Placement Rate (%): \"))\r\n#\r\n# Predict tuition fee\r\npredicted_fee = model.predict(np.array([[ranking, satisfaction, placement]]))\r\nprint(\"\\nPredicted Annual Tuition Fee: $\", round(predicted_fee[0], 2))\r\n\r\nalpha=model.intercept_\r\n# print(alpha)\r\nbeta=model.coef_\r\n# print(beta[0])\r\n# print(beta[1])\r\n# print(beta[2])\r\nformula_fee=alpha+(beta[0]*ranking)+(beta[1]*satisfaction)+(beta[2]*placement)\r\n\r\nprint(\"\\nPredicted Annual Tuition Fee accroding to formula: $\", round(formula_fee, 2))<\/pre>\n <\/span><\/p>\n","protected":false},"excerpt":{"rendered":"Program 1 College Dataset # To build a machine learning model that can predict the annual tuition fee of a # private college based on: # Its ranking , The student satisfaction score ,...<\/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":[8431,34745,33127,33128,20697,34749,34746,34747,34748],"class_list":["post-145676","post","type-post","status-publish","format-standard","hentry","category-machine-learning","tag-machine-learning","tag-machine-learning-multiple-linear-regression-model-for-predicting-annual-tuition-fee","tag-machine-learning-practical","tag-machine-learning-program","tag-machine-learning-project","tag-multiple-linear-regression-model","tag-multiple-linear-regression-model-for-predicting-annual-tuition-fee","tag-multiple-linear-regression-model-for-predicting-annual-tuition-fee-using-machine-learning","tag-predicting-annual-tuition-fee"],"yoast_head":"\n
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