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Summary

Summary

Description
English: This notebook illustrates one of the basic concepts in ensemble learning.

By combining classifiers that are trained on different subsets of the training data, it is possible to achieve superior classifier performance.

The figure is adapted from an example published in:

Code to produce this image is available at: https://gist.github.com/smihael/60b101c0f04ba869da2fb345c6ae3aa3
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Author Smihael
Other versions Slovene version

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Illustration of combining several classification models

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11 February 2024

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8a4f095456a56330c12bbcaa22a167b055d350a2

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current19:55, 11 February 2024Thumbnail for version as of 19:55, 11 February 20241,080 × 736 (353 KB)Smihael=={{int:filedesc}}== {{Information |description={{en|1=This notebook illustrates one of the basic concepts in ensemble learning. By combining classifiers that are trained on different subsets of the training data, it is possible to achieve superior classifier performance. The figure is adapted from an example published in: * Robi Polikar. Ensemble based systems in decision making. Circuits and Systems Magazine, IEEE, 6(3):21–45, 2006. Link to the original publication: https://doi.org/10.110...

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