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minmax not absmax in docs

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Cuong Duong 2023-10-18 18:33:05 +11:00
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docs/_docs/additional_topics.md
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@ -240,7 +240,7 @@ There are few caveats that should be kept in mind when considering warm-starting
Before model fitting, Prophet scales `y` by dividing by the maximum value in the history. For datasets with very large `y` values, the scaled `y` values may be compressed to a very small range (i.e. `[0.99999... - 1.0]`), which causes a bad fit. This can be fixed by setting `scaling='absmax'` in the Prophet constructor.
Before model fitting, Prophet scales `y` by dividing by the maximum value in the history. For datasets with very large `y` values, the scaled `y` values may be compressed to a very small range (i.e. `[0.99999... - 1.0]`), which causes a bad fit. This can be fixed by setting `scaling='minmax'` in the Prophet constructor.
```python

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notebooks/additional_topics.ipynb
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@ -437,7 +437,7 @@
"source": [
"### minmax scaling (new in 1.1.5)\n",
"\n",
"Before model fitting, Prophet scales `y` by dividing by the maximum value in the history. For datasets with very large `y` values, the scaled `y` values may be compressed to a very small range (i.e. `[0.99999... - 1.0]`), which causes a bad fit. This can be fixed by setting `scaling='absmax'` in the Prophet constructor."
"Before model fitting, Prophet scales `y` by dividing by the maximum value in the history. For datasets with very large `y` values, the scaled `y` values may be compressed to a very small range (i.e. `[0.99999... - 1.0]`), which causes a bad fit. This can be fixed by setting `scaling='minmax'` in the Prophet constructor."
]
},
{