Gradient Boosting Machine is a popular ensemble machine learning method. It uses a series of weak models sequentially to improve the model's performance based on the errors of the previous model. The idea is to find out if there is any pattern in the residuals or errors and use that to improve the model's performance further.
In my last video, I explained the intuition behind the Gradient Boosting Machine. If you haven't watched it, please check it out:
• Gradient Boosting Mach...
Here is the documentation on the Gradient Boosting Machine Classifier:
scikit-learn.org/stable/modul...
The dataset used in this tutorial is here:
github.com/rashida048/Machine...
The complete code used in this tutorial:
github.com/rashida048/Machine...
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