minmax not absmax in docs

qododavid · Oct 18, 2023 · c00f6a2 · c00f6a2
1 parent b16d849
commit c00f6a2
Show file tree

Hide file tree

Showing 2 changed files with 2 additions and 2 deletions.
diff --git a/docs/_docs/additional_topics.md b/docs/_docs/additional_topics.md
@@ -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

diff --git a/notebooks/additional_topics.ipynb b/notebooks/additional_topics.ipynb
@@ -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."
    ]
   },
   {
Original file line number	Diff line number	Diff line change
Expand Up		@@ -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
Expand Down