---
title: "Supervised vs unsupervised learning"
subject: "Data Mining"
chapter: 3
key: "semester_7/data_mining:supervised-vs-unsupervised"
source: https://www.bctengineer.com/q/semester_7/data_mining/supervised-vs-unsupervised
site: BCT Engineering
---

# Supervised vs unsupervised learning

Data Mining · Chapter 3: Classification

- Asked in: year not given
- Video: [Lec-23: Supervised vs Unsupervised learning with real life example](https://www.youtube.com/watch?v=fM8XdC1EweU) — Gate Smashers
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_7/data_mining/supervised-vs-unsupervised
- Whole chapter: https://www.bctengineer.com/md/semester_7/data_mining/chapter-3

## Question

Differentiate supervised and unsupervised learning with suitable examples.

## Short answer

Supervised learning uses labeled data to predict outputs (e.g., spam detection), while unsupervised learning finds patterns in unlabeled data (e.g., customer segmentation). Supervised tasks include classification and regression; unsupervised includes clustering and association.

## Answer

**Supervised learning** learns from training data that contains the correct output (class label) for each input, and builds a model to predict labels for new data. **Unsupervised learning** works on data without labels and finds hidden structure or groups by itself.

| Basis | Supervised learning | Unsupervised learning |
| --- | --- | --- |
| Training data | Labelled (input and known output) | Unlabelled (input only) |
| Goal | Predict a class or value | Discover patterns and groups |
| Supervision | A "teacher" gives the correct answer | None |
| Main tasks | Classification, regression | Clustering, association, dimensionality reduction |
| Evaluation | Accuracy on test set, easy to measure | Harder, uses cluster quality measures |
| Number of classes | Known in advance | Not known (or chosen, e.g. k) |
| Algorithms | Decision tree, Naive Bayes, KNN, SVM, neural network | k-means, hierarchical, DBSCAN, Apriori, PCA |
| Example | Predict if an email is spam from emails already marked spam/not spam | Group customers into segments by buying behaviour |

A third type, **semi-supervised learning**, uses a few labelled and many unlabelled examples.

## Check yourself

The answer's key points as multiple-choice questions, with the correct option and why.

1. What is the main difference in training data?
   A. Supervised uses unlabelled data
   B. Both use labelled data
   C. Supervised uses labelled data; unsupervised uses unlabelled data
   D. Unsupervised uses a teacher
   Answer: C. Labels are the supervision. (Key point: Training data)

2. Which pair is correct?
   A. Supervised: k-means; unsupervised: decision tree
   B. Supervised: Apriori; unsupervised: KNN
   C. Both: SVM
   D. Supervised: decision tree; unsupervised: k-means
   Answer: D. Classification/regression are supervised; clustering/association unsupervised. (Key point: Examples)

3. How is the number of classes treated in unsupervised learning?
   A. Not known in advance (or chosen, e.g. k)
   B. Always known
   C. Always two
   D. Given by labels
   Answer: A. Supervised learning knows classes in advance. (Key point: Number of classes)

4. Semi-supervised learning uses:
   A. Only labelled examples
   B. A few labelled and many unlabelled examples
   C. Only unlabelled examples
   D. No data
   Answer: B. A third type between the two. (Key point: Semi-supervised)

## Related in Data Mining

- [Need of clustering; hierarchical vs partitioning; K-means](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Acluster-need-hier-vs-partition-kmeans) — Data Mining, chapter 5
- [Descriptive vs predictive data mining](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adm-descriptive-predictive) — Data Mining, chapter 1
- [Data warehouse vs database](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adw-vs-database) — Data Mining, chapter 1
- [OLAP vs OLTP; data cube, operations](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Aolap-oltp-data-cube-fact-dimension) — Data Mining, chapter 2
- [OLAP vs OLTP; schema, fact, dimension](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Aolap-oltp-schema-fact-dimension) — Data Mining, chapter 2
- [OLAP vs OLTP; schema modeling; star DMQL](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Aolap-oltp-schema-star-dmql) — Data Mining, chapter 2

## Related in other subjects

- [Neural network; supervised vs unsupervised](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Ann-supervised-unsupervised) — Artificial Intelligence, chapter 6
- [Short note: supervised vs unsupervised](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Asupervised-vs-unsupervised-note) — Artificial Intelligence, chapter 6
- [Knowledge vs learning, acting humanly](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Aknowledge-vs-learning-acting-humanly) — Artificial Intelligence, chapter 1
- [GA vs fuzzy based learning](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Aga-vs-fuzzy-learning) — Artificial Intelligence, chapter 6