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開始行:
[[UTAPwiki/セミナー/宇宙物理学セミナー]]
Tilman Hartwig
Title: Machine Learning for Classification of Astronomica...
Abstract:
I will give an overview of various machine learning methods
and their scientific applications. As one specific exampl...
present decision trees in more detail since they are a ve...
method to classify astronomical data: a labelled training...
split according to available features by requiring that e...
minimises the information entropy of the assigned classes...
mathematical formulation allows us to construct decision ...
supervised learning, which can then be applied to classif...
Eventually, I will present recent results of my own resea...
classifying the chemical abundance patterns of metal-poor...
Milky Way, we can derive the multiplicity of the first ge...
stars in the Universe. Furthermore, this approach provide...
importance to identify crucial chemical elements to class...
stars, which can be used to optimise future spectroscopic...
終了行:
[[UTAPwiki/セミナー/宇宙物理学セミナー]]
Tilman Hartwig
Title: Machine Learning for Classification of Astronomica...
Abstract:
I will give an overview of various machine learning methods
and their scientific applications. As one specific exampl...
present decision trees in more detail since they are a ve...
method to classify astronomical data: a labelled training...
split according to available features by requiring that e...
minimises the information entropy of the assigned classes...
mathematical formulation allows us to construct decision ...
supervised learning, which can then be applied to classif...
Eventually, I will present recent results of my own resea...
classifying the chemical abundance patterns of metal-poor...
Milky Way, we can derive the multiplicity of the first ge...
stars in the Universe. Furthermore, this approach provide...
importance to identify crucial chemical elements to class...
stars, which can be used to optimise future spectroscopic...
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