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| author | TheSiahxyz <164138827+TheSiahxyz@users.noreply.github.com> | 2024-04-29 22:06:12 -0400 |
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| committer | TheSiahxyz <164138827+TheSiahxyz@users.noreply.github.com> | 2024-04-29 22:06:12 -0400 |
| commit | 4d53fa14ee0cd615444aca6f6ba176e0ccc1b5be (patch) | |
| tree | 4d9f0527d9e6db4f92736ead0aa9bb3f840a0f89 /SI/Resource/Data Science/Machine Learning/Contents/Classification.md | |
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diff --git a/SI/Resource/Data Science/Machine Learning/Contents/Classification.md b/SI/Resource/Data Science/Machine Learning/Contents/Classification.md new file mode 100644 index 0000000..12c125e --- /dev/null +++ b/SI/Resource/Data Science/Machine Learning/Contents/Classification.md @@ -0,0 +1,17 @@ +--- +id: 2023-12-17 +aliases: December 17, 2023 +tags: +- link-note +- Data-Science +- Machine-Learning +- Classification +--- + +# Classification + +Classification in the context of machine learning and statistics is a type of supervised learning approach where the output variable is a category, such as "spam" or "not spam", or "disease" and "no disease". In classification, an algorithm is trained on a dataset of labeled examples, learning to associate input data points with the corresponding category label. Once trained, the model can then categorize new, unseen data points. + +1. Input: Continuous (float), Discrete (categorical), etc. +2. Output: Discrete (categorical) +3. Model types: Binary - [[Sigmoid]], polynomial - [[softmax]]
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