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@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 38cef46b6802d559794f4317c62c8a58
+config: 969f05cbbb6cecf30f178e6e35af0c26
 tags: 645f666f9bcd5a90fca523b33c5a78b7
@@ -4,7 +4,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n# Demo of OPTICS clustering algorithm\n\n.. currentmodule:: sklearn\n\nFinds core samples of high density and expands clusters from them.\nThis example uses data that is generated so that the clusters have\ndifferent densities.\nThe :class:`~cluster.OPTICS` is first used with its Xi cluster detection\nmethod, and then setting specific thresholds on the reachability, which\ncorresponds to :class:`~cluster.DBSCAN`. We can see that the different\nclusters of OPTICS's Xi method can be recovered with different choices of\nthresholds in DBSCAN.\n"
+        "\n# Demo of OPTICS clustering algorithm\n\n.. currentmodule:: sklearn\n\nFinds core samples of high density and expands clusters from them.\nThis example uses data that is generated so that the clusters have\ndifferent densities.\n\nThe :class:`~cluster.OPTICS` is first used with its Xi cluster detection\nmethod, and then setting specific thresholds on the reachability, which\ncorresponds to :class:`~cluster.DBSCAN`. We can see that the different\nclusters of OPTICS's Xi method can be recovered with different choices of\nthresholds in DBSCAN.\n"
       ]
     },
     {
 
@@ -8,6 +8,7 @@
 Finds core samples of high density and expands clusters from them.
 This example uses data that is generated so that the clusters have
 different densities.
+
 The :class:`~cluster.OPTICS` is first used with its Xi cluster detection
 method, and then setting specific thresholds on the reachability, which
 corresponds to :class:`~cluster.DBSCAN`. We can see that the different
Original file line number	Diff line number	Diff line change
`@@ -4,7 +4,7 @@`
`4`	`4`	`"cell_type": "markdown",`
`5`	`5`	`"metadata": {},`
`6`	`6`	`"source": [`
`7`		- "\n# Demo of OPTICS clustering algorithm\n\n.. currentmodule:: sklearn\n\nFinds core samples of high density and expands clusters from them.\nThis example uses data that is generated so that the clusters have\ndifferent densities.\nThe :class:`~cluster.OPTICS` is first used with its Xi cluster detection\nmethod, and then setting specific thresholds on the reachability, which\ncorresponds to :class:`~cluster.DBSCAN`. We can see that the different\nclusters of OPTICS's Xi method can be recovered with different choices of\nthresholds in DBSCAN.\n"
	`7`	+ "\n# Demo of OPTICS clustering algorithm\n\n.. currentmodule:: sklearn\n\nFinds core samples of high density and expands clusters from them.\nThis example uses data that is generated so that the clusters have\ndifferent densities.\n\nThe :class:`~cluster.OPTICS` is first used with its Xi cluster detection\nmethod, and then setting specific thresholds on the reachability, which\ncorresponds to :class:`~cluster.DBSCAN`. We can see that the different\nclusters of OPTICS's Xi method can be recovered with different choices of\nthresholds in DBSCAN.\n"
`8`	`8`	`]`
`9`	`9`	`},`
`10`	`10`	`{`