Classification vs Regression
1. Title: “The Startup Duo – Sam & Riya’s Data Adventure”
Learning when to use classification or regression, the real-world way.
Scene 1: Riya – The HR Analyst (Classification)
Riya works in a growing company’s HR analytics team. Her job? To predict which job applicants are likely to leave within a year of hiring.
She collects data from resumes and employee records:
- Years of experience
- Education level
- Past job switch frequency
- Distance from home
And the goal is simple: “Will this candidate leave within a year? Yes or No?”
She’s predicting a label — either “Stay” or “Leave”. There’s no in-between.
This is a Classification Problem.
Scene 2: Sam – The Product Manager (Regression)
Sam is launching a new subscription-based mobile app. He wants to predict how much revenue a user might generate in 6 months after signing up.
His dataset has:
- App usage frequency
- In-app purchases
- Device type
- Age of user
- First session duration
He wants to predict: “How much money will this user bring in?” – like ₹350.50 or ₹1027.00
This is predicting a number, not a label. So this is a Regression Problem.
They simply ask: “Do we want a category (label) or a continuous number?”
2. Classification – Real-Life Scenarios
| Use Case | Description |
|---|---|
| Mental Health App | Predict if a user is at risk of depression (Yes/No) based on daily check-ins |
| E-Commerce | Predict whether a user will buy or not buy after browsing for 10 minutes |
| Customer Service | Predict if a customer chat is positive, neutral, or negative using sentiment data |
| Auto Insurance | Predict if a person is eligible for premium insurance based on driving behavior |
| Hiring Platform | Predict if a candidate is a good fit, average, or not suitable for a role |
3. Regression – Real-Life Scenarios
| Use Case | Description |
|---|---|
| Marketing Analytics | Predict how much budget to allocate for a campaign to maximize ROI |
| Health Monitoring | Predict a patient’s blood sugar level based on diet, sleep, and activity |
| Real Estate | Predict the rent of a property based on location, size, and facilities |
| EdTech Platform | Predict a student’s score in the next test based on learning patterns |
| Ride-Hailing App | Predict estimated fare for a route based on time, distance, and demand |
4. Decision Cheat Sheet (Real-Life Rule of Thumb)
| If you want to… | Use |
|---|---|
| Assign a group, category, or tag to something | Classification |
| Forecast a value, a score, or a quantity | Regression |
5. Bonus: Real-World Questions → Problem Type
| Question | Problem Type |
|---|---|
| Will this customer churn next month? | Classification |
| How many units will we sell next quarter? | Regression |
| What is the risk level of this insurance application? (Low/Medium/High) | Classification |
| What price should we offer for a new home loan? | Regression |
| Which department should handle this support ticket? | Classification |
| How much electricity will this household consume next month? | Regression |
Classification vs Regression – Visual Roadmap