# Weak Learning, Boosting, and the AdaBoost algorithm

DevFeed: [Weak Learning, Boosting, and the AdaBoost algorithm](<https://devfeed.tech/articles/weak-learning-boosting-and-the-adaboost-algorithm-40383.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2015/05/18/boosting-census/>)

Published: 2015-05-18T09:00:00Z

Content type: tutorial

Language: en

Sources: [Jeremy Kun](<https://devfeed.tech/sources/jeremy-kun.md>)

Topics: [Algorithm](<https://devfeed.tech/topics/algorithm.md>), [Learning](<https://devfeed.tech/topics/learning.md>)

Tags: [algorithm](<https://devfeed.tech/tags/algorithm.md>), [better](<https://devfeed.tech/tags/better.md>), [boosting](<https://devfeed.tech/tags/boosting.md>), [classification](<https://devfeed.tech/tags/classification.md>), [distribution](<https://devfeed.tech/tags/distribution.md>), [efficiently](<https://devfeed.tech/tags/efficiently.md>), [function](<https://devfeed.tech/tags/function.md>), [learner](<https://devfeed.tech/tags/learner.md>), [learning](<https://devfeed.tech/tags/learning.md>), [models](<https://devfeed.tech/tags/models.md>), [number](<https://devfeed.tech/tags/number.md>), [pac-learning](<https://devfeed.tech/tags/pac-learning.md>), [re](<https://devfeed.tech/tags/re.md>), [runtime](<https://devfeed.tech/tags/runtime.md>)

## AI overview

This article introduces learning models in the context of Probably Approximately Correct (PAC) learning and compares the usual PAC model with weak PAC learning. It explains that weak learning requires accuracy only slightly better than random guessing and states that weak and strong learning are equivalent.

## Source excerpt

When addressing the question of what it means for an algorithm to learn, one can imagine many different models, and there are quite a few. This invariably raises the question of which models are "the same" and which are "different," along with a precise description of how we're comparing models. We've seen one learning model so far, called Probably Approximately Correct (PAC), which espouses the following answer to the learning question: