Adaboost

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

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