Questions tagged [gradient-boosting]

For questions related to gradient boosting, which is a machine learning technique that can be used for regression and classification problems and which produces a prediction model in the form of an ensemble of other smaller prediction models (typically decision trees).

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How do weak learners become strong in boosting?

Boosting refers to a family of algorithms which converts weak learners to strong learners. How does it happen?
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GPU-training on Google Cloud Platform slower than CPU-training

I recently trained Kaggles "Advanced Housing Prices"-Competition using Catboost. For training i used a compute-instance on Google Cloud Platform (GCP) (CPU: Xeon Quad-Core, RAM: 15GB, GPU: ...
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How would the “best function” been constructed if there are no computationally limitations?

I am reading the Wikipedia article on gradient boosting. There is written: Unfortunately, choosing the best function $h$ at each step for an arbitrary loss function $L$ is a computationally ...
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How can I use gradient boosting with multiple features?

I'm trying to use gradient boosting and I'm using sklearn's GradientBoostingClassifier class. My problem is that I'm having a data frame with 5 columns and I want ...