- 2074 Bhadra · 4 marks
Short note: supervised vs unsupervised
Short answer
Supervised learning uses labelled data to predict outputs (e.g., classification), while unsupervised learning finds hidden patterns in unlabelled data (e.g., clustering). Supervised has error feedback; unsupervised has no teacher.
Write a short note on supervised versus unsupervised learning.
Supervised learning trains a model on labelled data, where each input has the correct output (target). The model learns the mapping and the error between prediction and target is used to adjust it. Tasks: classification (spam / not spam) and regression (house price). Algorithms: perceptron, back-propagation, decision trees, SVM, k-NN.
Unsupervised learning works on unlabelled data. The model finds hidden structure by itself, such as clusters, similarities or lower-dimensional representations. Tasks: clustering, association, dimensionality reduction. Algorithms: k-means, Kohonen SOM, competitive learning, PCA.
| Point | Supervised | Unsupervised |
|---|---|---|
| Data | Labelled | Unlabelled |
| Teacher/feedback | Yes (error signal) | No |
| Goal | Predict output | Discover patterns |
| Accuracy check | Easy, against known labels | Hard, no ground truth |
| Example | Handwritten digit recognition | Customer segmentation |
A third type, reinforcement learning, learns from rewards and penalties.
✓ Answer checked by Claude Opus 5.5 (high effort)
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