Merge pull request #46 from NiklasGustafsson/main

NiklasGustafsson · web-flow · commit 1218eaa957ea · 2023-06-25T13:05:10.000-07:00
Updated tutorial comments on 'Multinomial'
diff --git a/tutorials/CSharp/tutorial4.ipynb b/tutorials/CSharp/tutorial4.ipynb
@@ -218,7 +218,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "There's a class corresponding to 'Multinomial' for categorical distributions. Here, the category is denoted by the index into the tensor. For sample sizes of at least one dimension, the innermost dimension (the last index) representes the category. In other words, each row is a sample, each column is a category. The value in each cell is how many times (out of the total count specified) that the category was selected."
+    "Like 'Binomial' for binary distributions, there's a class 'Multinomial' for categorical distributions that aren't binary. Here, the category is denoted by the index into the tensor. For sample sizes of at least one dimension, the innermost dimension (the last index) representes the category. In other words, each row is a sample, each column is a category. The value in each cell is how many times (out of the total count specified) that the category was selected."
    ]
   },
   {
diff --git a/tutorials/FSharp/tutorial4.ipynb b/tutorials/FSharp/tutorial4.ipynb
@@ -219,7 +219,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "There's a class corresponding to 'Multinomial' for categorical distributions. Here, the category is denoted by the index into the tensor. For sample sizes of at least one dimension, the innermost dimension (the last index) representes the category. In other words, each row is a sample, each column is a category. The value in each cell is how many times (out of the total count specified) that the category was selected."
+    "Like 'Binomial' for binary distributions, there's a class 'Multinomial' for categorical distributions that aren't binary. Here, the category is denoted by the index into the tensor. For sample sizes of at least one dimension, the innermost dimension (the last index) representes the category. In other words, each row is a sample, each column is a category. The value in each cell is how many times (out of the total count specified) that the category was selected."
    ]
   },
   {

Original file line number	Diff line number	Diff line change
`@@ -218,7 +218,7 @@`
`218`	`218`	`"cell_type": "markdown",`
`219`	`219`	`"metadata": {},`
`220`	`220`	`"source": [`
`221`		`- "There's a class corresponding to 'Multinomial' for categorical distributions. Here, the category is denoted by the index into the tensor. For sample sizes of at least one dimension, the innermost dimension (the last index) representes the category. In other words, each row is a sample, each column is a category. The value in each cell is how many times (out of the total count specified) that the category was selected."`
	`221`	`+ "Like 'Binomial' for binary distributions, there's a class 'Multinomial' for categorical distributions that aren't binary. Here, the category is denoted by the index into the tensor. For sample sizes of at least one dimension, the innermost dimension (the last index) representes the category. In other words, each row is a sample, each column is a category. The value in each cell is how many times (out of the total count specified) that the category was selected."`
`222`	`222`	`]`
`223`	`223`	`},`
`224`	`224`	`{`
Original file line number	Diff line number	Diff line change
`@@ -219,7 +219,7 @@`
`219`	`219`	`"cell_type": "markdown",`
`220`	`220`	`"metadata": {},`
`221`	`221`	`"source": [`
`222`		`- "There's a class corresponding to 'Multinomial' for categorical distributions. Here, the category is denoted by the index into the tensor. For sample sizes of at least one dimension, the innermost dimension (the last index) representes the category. In other words, each row is a sample, each column is a category. The value in each cell is how many times (out of the total count specified) that the category was selected."`
	`222`	`+ "Like 'Binomial' for binary distributions, there's a class 'Multinomial' for categorical distributions that aren't binary. Here, the category is denoted by the index into the tensor. For sample sizes of at least one dimension, the innermost dimension (the last index) representes the category. In other words, each row is a sample, each column is a category. The value in each cell is how many times (out of the total count specified) that the category was selected."`
`223`	`223`	`]`
`224`	`224`	`},`
`225`	`225`	`{`