AdaBoost

Concept and definition

AdaBoost

What is AdaBoost?

AdaBoost (Adaptive Boosting) is a supervised machine learning algorithm used to improve the accuracy of weak classification models. The AdaBoost algorithm iteratively trains a sequence of weak classifiers on different subsets of data, assigning higher weights to data that was misclassified in previous iterations. It then combines the results of these weak classifiers into a weighted strong classifier, with the best performing weak classifiers having a higher weight in the final classification.

The AdaBoost algorithm is known for its ability to significantly improve the accuracy of machine learning models, especially in complex classification tasks with large and noisy datasets. Moreover, it is easy to implement and can be adapted to different types of weak machine learning algorithms, which makes it popular in machine learning practice.

« Back to glossary

Do you want to get in touch?

CDRs contain data that a telecommunications company collects about phone calls, such as time and length of call. This data can be used in analytical applications.
Fill the form
Share:
How to increase a company's sales

All businesses usually plan for annual growth, although not all of them achieve it. Increasing the sales of a company in 2022 is [...]

Read More »
What is Natural Language Processing?

Natural Language Processing or NLP analyzes how machines understand, interpret and process human language.

Read More »
OpenAI: What is it, how to use it and what can you do with this artificial intelligence?

OpenAI is a technology company created by the main leaders in artificial intelligence that, in its beginnings, defined itself as an organization that [...]

Read More »
Clustering for data analysis

Clustering methods, or grouping, are a fundamental part of the data analysis process, since they allow an automatic segmentation of the data [...]

Read More »
See more entries
© Gamco 2021, All Rights Reserved - Legal notice - Privacy - Cookies