What are the differences between LightGBM and FastTree algorithms used by ML.Net's modelbuilder?

Glenn Edson Bergstrøm 1 Reputation point

For my master thesis, I am using ML.Net library with the model builder to build machine learning models for regression / to predict values. My field of study is in constructional mechanics, so I'm rather new to machine learning.

For most of my models, tree-based regression algorithms seem to be the best performing, and of these LightGBM and FastTree are the best performing algorithms.

I've tried to read up on LightGBM here: https://www.microsoft.com/en-us/research/publication/lightgbm-a-highly-efficient-gradient-boosting-decision-tree/ And FastTree here: https://learn.microsoft.com/en-us/dotnet/api/microsoft.ml.trainers.fasttree.fasttreeregressiontrainer?view=ml-dotnet

However, I struggle to distinguish what the difference between these algorithms is. Could someone explain what the difference between LightGBM and FastTree is?

Azure Machine Learning
Azure Machine Learning
An Azure machine learning service for building and deploying models.
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.NET Machine learning
.NET Machine learning
.NET: Microsoft Technologies based on the .NET software framework.Machine learning: A type of artificial intelligence focused on enabling computers to use observed data to evolve new behaviors that have not been explicitly programmed.
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  1. YutongTie-MSFT 43,076 Reputation points


    Thanks for reaching out to us! The right place for ML.NET related question is the GitHub forum here, and the Gitter community. Sorry for the inconveniences.


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