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Ensemble learning: A survey

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Ensemble methods are considered the state‐of‐the art solution for many machine learning challenges. Such methods improve the predictive performance of a single model by training multiple models and combining their predictions. This paper introduce the concept of ensemble learning, reviews traditional, novel and state‐of‐the‐art ensemble methods and discusses current challenges and trends in the field.

This article is categorized under:

  • Algorithmic Development > Model Combining
  • Technologies > Machine Learning
  • Technologies > Classification
Number of published papers per year, based on searching the terms “ensemble” together with “machine learning” in the “web of science” database
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Number of technical posts per method between 2014 and 2017. Posts were collected from stackexchange statistical and data science forums. We consider messages that contain the name of the method
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Number of published papers per method over time. Based on “web of science” database
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Technologies > Machine Learning
Algorithmic Development > Model Combining
Technologies > Classification

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