Ensemble Classification from Multiple Machine Learning Algorithms

Abstract

The ensemble is a machine learning classification technique that uses classifiers whose individual decisions are combined in some way to classify new examples. The ensemble approach is simplest, it generates multiple classifiers, and each classifier votes on the test instance. Here, the point is to take a basic unremarkable calculation and change it into a super classifier without requiring any extravagant new calculation. In this paper, the Ensemble technique is implemented in Google Colaboratory. Google Colaboratory is a cloud-based service which is also known as Colab. Google Colab is based on Jupyter Notebook where machine learning and deep learning concepts can be implementable. The Google Colab provides free access to GPU which is very much required to disseminate machine learning algorithms. This paper attempted how the ensemble technique can be implemented for the classification problem and also paper emphasis on how the voting system in the ensemble method gives better accuracy for the classification problem.