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fix(gds-community-detection): fix KMeans lessons using wrong property #445

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31 changes: 31 additions & 0 deletions ...c/courses/gds-community-detection/modules/3-kmeans/lessons/2-kmeans/lesson.adoc
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Original file line number Diff line number Diff line change
Expand Up @@ -117,6 +117,37 @@ include::questions/1-deterministic.adoc[leveloffset=+1]

include::questions/2-kmeans.adoc[leveloffset=+1]


== Troubleshooting

If you receive an error stating that the graph does not exist, you may need to recreate the `survey` graph projection from the link:/courses/gds-community-detection/3-kmeans/1-scaling/[Feature normalization^] lesson.

.Recreate the graph projection
[%collapsible]
====
[source,cypher]
----
CALL gds.graph.drop('survey', false);

CALL gds.graph.project(
'survey',
'Person',
'*',
{nodeProperties:['vector']}
);

CALL gds.scaleProperties.mutate(
'survey',
{
nodeProperties: ['vector'],
scaler: 'MinMax',
mutateProperty: 'scaledVector'
}
);
----
====


[.summary]
== Summary

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35 changes: 33 additions & 2 deletions ...ses/gds-community-detection/modules/3-kmeans/lessons/3-optimization/lesson.adoc
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Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,7 @@ You will use the *stats* mode of the algorithm as you are only interested in the
----
UNWIND range(5,20) AS k
CALL gds.beta.kmeans.stats('survey',
{k:k, nodeProperty:'vector', computeSilhouette: True})
{k:k, nodeProperty:'scaledVector', computeSilhouette: true})
YIELD averageDistanceToCentroid, averageSilhouette
RETURN k, averageDistanceToCentroid, averageSilhouette
ORDER BY averageSilhouette DESC LIMIT 3;
Expand All @@ -48,7 +48,7 @@ In this example, you will use the `numberOfRestarts` value 5.
[source,cypher]
----
CALL gds.beta.kmeans.write('survey',
{k:5, nodeProperty:'vector',
{k:5, nodeProperty:'scaledVector',
numberOfRestarts: 5,
writeProperty:'kmeans5'})
----
Expand All @@ -61,6 +61,37 @@ CALL gds.beta.kmeans.write('survey',
include::questions/1-metric.adoc[leveloffset=+1]
include::questions/2-restarts.adoc[leveloffset=+1]


== Troubleshooting

If you receive an error stating that the graph does not exist, you may need to recreate the `survey` graph projection from the link:/courses/gds-community-detection/3-kmeans/1-scaling/[Feature normalization^] lesson.

.Recreate the graph projection
[%collapsible]
====
[source,cypher]
----
CALL gds.graph.drop('survey', false);

CALL gds.graph.project(
'survey',
'Person',
'*',
{nodeProperties:['vector']}
);

CALL gds.scaleProperties.mutate(
'survey',
{
nodeProperties: ['vector'],
scaler: 'MinMax',
mutateProperty: 'scaledVector'
}
);
----
====


[.summary]
== Summary

Expand Down