---
title: "What is the difference between supervised learning and unsupervised learning?"  
description: "What is the difference between supervised learning and unsupervised learning?"  
author: "Revati S Misra"  
published: 2023-05-28  
updated: 2023-05-29  
canonical: https://www.mindstick.com/forum/158510/what-is-the-difference-between-supervised-learning-and-unsupervised-learning  
category: "big data"  
tags: ["bigdata", "machine learning", "data science"]  
reading_time: 3 minutes  

---

# What is the difference between supervised learning and unsupervised learning?

What is the [difference between supervised](https://www.mindstick.com/forum/161509/what-is-the-difference-between-supervised-unsupervised-and-semi-supervised-learning) learning and [unsupervised learning](https://www.mindstick.com/forum/161477/explain-the-difference-between-supervised-and-unsupervised-learning)?

## Replies

### Reply by Aryan Kumar

[Supervised learning](https://www.mindstick.com/blog/302851/supervised-learning-predictive-modeling-and-classification-techniques) and unsupervised learning are two of the most common types of machine learning. In supervised learning, the model is trained on a set of labeled data, which means that each data point has a corresponding output. The model then learns to predict the output for new data points. In unsupervised learning, the model is trained on a set of unlabeled data, which means that the model does not know what the output should be. The model then learns to find patterns in the data.

Here is a table that summarizes the key differences between supervised learning and unsupervised learning:

| Feature | Supervised Learning | Unsupervised Learning |
| --- | --- | --- |
| Data | Labeled | Unlabeled |
| Goal | Predict output | Find patterns |
| Example | Spam filtering | Clustering |

Supervised learning is typically used for tasks where the output is known, such as classification and regression. Unsupervised learning is typically used for tasks where the output is unknown, such as clustering and dimensionality reduction.

Here are some examples of supervised learning tasks:

- **Spam filtering**: Classifying emails as spam or not spam
- **Image classification**: Classifying images of objects, such as cars or dogs
- **Text classification**: Classifying text documents, such as news articles or product reviews
- **Regression**: Predicting a continuous value, such as the price of a house or the number of sales in a month

Here are some examples of unsupervised learning tasks:

- **Clustering**: Finding groups of similar data points, such as customers who are likely to buy the same products
- **Dimensionality reduction**: Reducing the number of features in a dataset, such as reducing the number of pixels in an image
- **Association rule mining**: Finding rules that describe relationships between items, such as which products are often bought together

Supervised learning is typically more accurate than unsupervised learning, but it requires more labeled data. Unsupervised learning is typically less accurate than supervised learning, but it can be used with unlabeled data.

The best type of machine learning to use depends on the specific task. If the output is known and there is a large amount of labeled data available, then supervised learning is the best choice. If the output is unknown or there is not enough labeled data available, then unsupervised learning may be a better choice.


---

Original Source: https://www.mindstick.com/forum/158510/what-is-the-difference-between-supervised-learning-and-unsupervised-learning

Copyright © MindStick Software Pvt. Ltd. This Markdown version is provided for developers, AI systems, and offline reading.