AdaBoost, which stands for Adaptive Boosting, is an ensemble learning algorithm that combines multiple weak learners (e.g., decision trees) to create a strong, accurate model. It is an iterative ...

AdaBoost can be used to solve a variety of real-world problems, such as predicting customer churn and classifying the types of topics customers are talking/calling about. The algorithm is heavily ...

ABSTRACT: Because of the increasing attention on environmental issues, especially air pollution, predicting whether a day is polluted or not is necessary to people’s health. In order to solve this ...

In Machine Learning context, there are typically two kinds of learners or algorithms, ones that learn well the correlations and gives out strong predictions and the ones which are lazy and gives out ...