[lucene-solr] branch SOLR-13105-visual updated: SOLR-13105: machine learning docs 26

[jb...@apache.org]

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jbernste pushed a commit to branch SOLR-13105-visual
in repository https://gitbox.apache.org/repos/asf/lucene-solr.git


The following commit(s) were added to refs/heads/SOLR-13105-visual by this push:
     new 9443f77  SOLR-13105: machine learning docs 26
9443f77 is described below

commit 9443f7714e8e0b9494bd287314d9ef8ce9ddaa35
Author: Joel Bernstein <jb...@apache.org>
AuthorDate: Thu Oct 3 09:33:28 2019 -0400

    SOLR-13105: machine learning docs 26
---
 solr/solr-ref-guide/src/machine-learning.adoc | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/solr/solr-ref-guide/src/machine-learning.adoc b/solr/solr-ref-guide/src/machine-learning.adoc
index d32652b..a83b7ed 100644
--- a/solr/solr-ref-guide/src/machine-learning.adoc
+++ b/solr/solr-ref-guide/src/machine-learning.adoc
@@ -589,8 +589,9 @@ The example demonstrates this capability by clustering and visualizing latitude
 In this example the `random` function draws a sample of records from the nyc311 (complaints database) collection where
 the complaint description matches "rat sighting" and latitude is populated in the record. The latitude and longitude fields
 are then vectorized and added as rows to a matrix. The matrix is transposed so each row contains a single latitude, longitude
-point. The `kmeans` function is then used to cluster the latitude and longitude points into 21 clusters. The `zplot` function
-is then used to visualize the clusters as a scatter plot.
+point. The `kmeans` function is then used to cluster the latitude and longitude points into 21 clusters.
+Finally, the `zplot` function
+is used to visualize the clusters as a scatter plot.
 
 image::images/math-expressions/2DCluster1.png[]