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--- sift:tutorials:run_k-means [2024/11/05 14:46] – wikisysop
+++ sift:tutorials:run_k-means [2024/11/05 14:58] (current) – wikisysop
@@ Line 1: / Line 1: @@
 ====== Run K-Means ======
-The k-means clustering algorithm is a commonly used method for grouping //n// individual data points into //k// clusters. It does so in an unsupervised manner, iteratively selecting cluster centre points and assigning data points to a cluster. Within Sift, this is implemented onto the [[sift:application:analyse_page#workspace_scores|PC transformed data]], after a PCA analysis is done. More information can be found on our [[sift:principal_component_analysis:using_principal_component_analysis_in_biomechanics|Using PCA in Biomechanics page]].
+The k-means clustering algorithm is a commonly used method for grouping //n// individual data points into //k// clusters. It does so in an unsupervised manner, iteratively selecting cluster centre points and assigning data points to a cluster. Within Sift, this is implemented onto the [[sift:application:analyse_page#workspace_scores|PC transformed data]], after a PCA analysis is done. More information about PCA can be found on our [[sift:principal_component_analysis:using_principal_component_analysis_in_biomechanics|Using PCA in Biomechanics page]].
 ==== The utility of clustering ====