Boosting and AdaBoost for Machine Learning

Boosting is an ensemble technique that attempts to create a strong classifier from a number of weak classifiers. In this post you will discover the AdaBoost Ensemble method for machine learning. After reading this post, you will know: What the boosting ensemble method is and generally how it works. How to learn to boost decision […]

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Bagging and Random Forest Ensemble Algorithms for Machine Learning

Random Forest is one of the most popular and most powerful machine learning algorithms. It is a type of ensemble machine learning algorithm called Bootstrap Aggregation or bagging. In this post you will discover the Bagging ensemble algorithm and the Random Forest algorithm for predictive modeling. After reading this post you will know about: The […]

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Ensemble Learning in R

  Guest post by Stefan Feuerriegel Previous research in data mining has devised numerous different algorithms for learning tasks. While an individual algorithm might already work decently, one can usually obtain a better predictive by combining several. This approach is referred to as ensemble learning. Common examples include random forests, boosting and AdaBost in particular. Our slide deck is positioned at the intersection of teaching the basic idea of ensemble learning and providing practical insights in R. Therefore, each algorithm comes with an easy-to-understand explanation on how to use it in R. We hope that the slide deck enables practitioners to quickly adopt ensemble learning for their applications in R. Moreover, the materials might lay the groundwork for courses on data mining and machine learning. Download the slides here: http://ift.tt/1Ufkymv Download the exercise sheet here: http://ift.tt/1XHbhkT

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Tune Machine Learning Algorithms in R (random forest case study)

It is difficult to find a good machine learning algorithm for your problem. But once you do, how do you get the best performance out of it. In this post you will discover three ways that you can tune the parameters of a machine learning algorithm in R. Walk through a real example step-by-step with […]

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How to Build an Ensemble Of Machine Learning Algorithms in R (ready to use boosting, bagging and stacking)

Ensembles can give you a boost in accuracy on your dataset. In this post you will discover how you can create three of the most powerful types of ensembles in R. This case study will step you through Boosting, Bagging and Stacking and show you how you can continue to ratchet up the accuracy of […]

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