AdaBoost is an example of which type of algorithm?

AdaBoost is a machine learning algorithm that falls under the category of boosting algorithms. Boosting is an ensemble technique that aims to create a strong classifier by combining multiple weak classifiers. Unlike bagging algorithms that train models independently, boosting algorithms train models sequentially, with each new model attempting to correct the errors made by the previous ones. This sequential learning process helps in improving the overall performance and accuracy of the model. AdaBoost, short for Adaptive Boosting, adjusts the weights of incorrectly classified instances, making them more significant for subsequent classifiers. Thus, it enhances the model's ability to focus on harder-to-classify examples. 🚀✨