Adaboost

Adaboost
Description	Adaboost is a boosting algorithm that combines multiple weak models into a single strong learner algorithm (the predictive model).
Why to use	To classify text into the possible categories.
When to use	When textual data needs to be classified.	When not to use	When the dataset does not contain textual data.
Prerequisites	The dataset should not contain any missing (NaN) values. The dataset should contain at least one categorical and one textual variable.
Input	Textual Data	Output	Classified data with predicted labels
Statistical Methods used	Accuracy Sensitivity Specificity F-score Confusion Matrix	Limitations	Weak classifiers (being too weak) may lead to overfitting Adaboost is sensitive to outliers