SHINY ADABOOSTING: AN INTERACTIVE DASHBOARD TO ADAPTIVE BOOSTING ALGORITHM

Autores

  • Mateus Maia Marques Universidade Federal da Bahia (UFBA)
  • Anderson Ara Universidade Federal da Bahia (UFBA)

Resumo

Boosting methods are becoming more and more popular due their outstanding performance when compared with some others statistical learning techniques. The Adaptive Boosting, or simply AdaBoost, was one of the first boosting techinques developed, and consists, generally, in a linear combination of weak models (models that peform slightly better than a random guess) to built a strong classifier. The main purpose of this article was to built an interactive application, using the Shiny R package, that possibilites the user to apply the AdaBoost model to some datasets and observe the behaviour of the model performance concerning parameter’s varation, base learners, presence of noise and others aspects as evaluating aspects as overfitting, accuracy and computational time.

Downloads

Não há dados estatísticos.

Downloads

Publicado

2019-07-02