Powered by Multiple Linear Regression trained on real employee data. Enter age & experience to get an accurate income estimate.
Try Prediction →Enter employee details to predict their income.
Your prediction result will appear here.
Key metrics from the trained Multiple Linear Regression model.
How the prediction works under the hood.
This model uses scikit-learn's LinearRegression to learn the relationship between two features (age and experience) and a target (income). The equation is:
Where β₀ is the intercept, β₁ is the age coefficient, and β₂ is the experience coefficient.
The model is trained on a dataset of 50 employee records containing age (23–59), experience (0–14 years), and annual income ($28k–$57k).
Data is split 80/20 into training and test sets with a fixed random seed for reproducibility.
This application is designed for deployment on Vercel using Vercel's Serverless Python runtime.
The Flask backend trains the model on startup, keeping it in memory for low-latency predictions.