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Implementation of Voting Classifiers in Scikit-learn and Python - Ensemble Machine Learning Tutorial
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In this machine learning tutorial, we explain how to implement voting classifiers in the Scikit-learn Python library. We explain the basics of ensemble learning and voting classifier. We dedicate special emphasis on the majority of vote strategy for selecting the optimal class. We then explain the Python implementation and provide a function for sketching the decision library. We use a linearly inseparable data set to illustrate the classification strategy. We use logistic regression, support vector machines, and random forests as base classifiers.
It takes a significant amount of time and energy to create these free video tutorials. You can support my efforts in this way:
- You Can also press the Thanks YouTube Dollar button
The webpage accompanying this tutorial is given here:
In this machine learning tutorial, we explain how to implement voting classifiers in the Scikit-learn Python library. We explain the basics of ensemble learning and voting classifier. We dedicate special emphasis on the majority of vote strategy for selecting the optimal class. We then explain the Python implementation and provide a function for sketching the decision library. We use a linearly inseparable data set to illustrate the classification strategy. We use logistic regression, support vector machines, and random forests as base classifiers.
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