---
id: 2023-12-17
aliases: December 17, 2023
tags:
- link-note
- Data-Science
- Machine-Learning
- Classification
---
# Classification

Classification in the context of machine learning and statistics is a type of supervised learning approach where the output variable is a category, such as "spam" or "not spam", or "disease" and "no disease". In classification, an algorithm is trained on a dataset of labeled examples, learning to associate input data points with the corresponding category label. Once trained, the model can then categorize new, unseen data points.

1. Input: Continuous (float), Discrete (categorical), etc.
2. Output: Discrete (categorical)
3. Model types: Binary - [[Sigmoid]], polynomial - [[softmax]]