GitHub repository: thomaswsu/Stochastic-Gradient-Boosting-and-Adaboost
Primary language: Jupyter Notebook
Created: 2020-11-12T21:34:35Z
Description: In this repository we evaluate the performance of Stochastic Boosting, Traditional Boosting, Gradient Descent, and Stochastic Gradient Descent methods in two ways. The first is through evaluating the amount of data needed for each method to effectively generalize the classification problem. The second is effect of increasing the complexity of Weak Learner. How does a Weak Learner perform as it becomes for complex? Is it still able to generalize the classification problem in the same number of epochs?