The presentation includes a Parallelized AdaBoost algorithm that is computed using iterative MapReduce by converting the data into a bipartite graph (slide 10-11). This project implements a ...

This repo has been created to supplement ideas and exercises from the free ebook Graph Algorithms: Practical Examples in Apache Spark & Neo4j: Whether you are building dynamic network models or ...

A new algorithm efficiently solves the graph isomorphism problem ... While the problem may seem abstract, it’s a prominent example of a strange class of puzzles that computers have trouble ...

Boosting algorithms combine multiple low accuracy models to create a high accuracy model. AdaBoost is example of Boosting algorithm. The important advantages of AdaBoost Low generalization error, easy ...

Abstract: Boosting is one of the algorithms which can boost the accuracy of weak classifiers, and Adaboost has been widely and successfully applied to classification, detection and data mining ...

Abstract: AdaBoost algorithm is proved to be a very efficient classification method for the balanced dataset with all classes having similar proportions. However, in real application, it is quite ...