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Adaboost: The Definitive Guide

Adaboost

AdaBoost, short for “Adaptive Boosting”, is the first practical boosting algorithm; it focuses on classification problems and aims to convert a set of weak classifiers into a strong one. It can be used in conjunction with many other types of learning algorithms to improve performance and advanced SEO services.

 1.Retrains the algorithm iteratively by choosing the training set based on the accuracy of previous training.

 2. The weight-age of each trained classifier at any iteration depends on the accuracy achieved.

adaboost 1

where f_m stands for the m_th weak classifier and theta_m is the corresponding weight. It is exactly the weighted combination of M weak classifiers.

Libraries require:

adaboost 2

Assigning a particular keyword and importing stopwords:

adaboost 3

Fetching the file and clearing them:

adaboost 4

Creating a term-document matrix:

adaboost 5

Creating clusters:

adaboost 6

 Function to execute the algorithm adaboost:

adaboost 7

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