Tool Cluster Analysis (Shapes)

K-Means cluster analysis using selected features from attributes table.

References

Forgy, E. (1965): Cluster Analysis of multivariate data: efficiency vs. interpretability of classifications. Biometrics 21:768.
Rubin, J. (1967): Optimal Classification into Groups: An Approach for Solving the Taxonomy Problem. J. Theoretical Biology, 15:103-144.

Author: O. Conrad (c) 2010
Menu: Shapes|Attributes

Parameters

	Name	Type	Identifier	Description	Constraints
Input	Shapes	shapes, input	`INPUT`	-	-
Output	Result (*)	shapes, output, optional	`RESULT`	-	-
Output	Statistics	table, output	`STATISTICS`	-	-
Options	Features	table fields	`FIELDS`	-	-
	Normalize	boolean	`NORMALISE`	-	Default: 0
	Cluster (*)	table field	`CLUSTER`	Target field for cluster numbers. If not set a new field will be added	-
	Method	choice	`METHOD`	-	Available Choices: [0] Iterative Minimum Distance (Forgy 1965) [1] Hill-Climbing (Rubin 1967) [2] Combined Minimum Distance / Hillclimbing Default: 1
	Number of Clusters	integer number	`NCLUSTER`	-	Minimum: 2 Default: 10
(*) optional

Command-line

Usage: saga_cmd table_tools 29 [-INPUT <str>] [-RESULT <str>] [-FIELDS <str>] [-NORMALISE <str>] [-CLUSTER <str>] [-STATISTICS <str>] [-METHOD <str>] [-NCLUSTER <num>]
  -INPUT:<str>     	Shapes
	shapes, input
  -RESULT:<str>    	Result
	shapes, output, optional
  -FIELDS:<str>    	Features
	table fields
  -NORMALISE:<str> 	Normalize
	boolean
	Default: 0
  -CLUSTER:<str>   	Cluster
	table field
  -STATISTICS:<str>	Statistics
	table, output
  -METHOD:<str>    	Method
	choice
	Available Choices:
	[0] Iterative Minimum Distance (Forgy 1965)
	[1] Hill-Climbing (Rubin 1967)
	[2] Combined Minimum Distance / Hillclimbing
	Default: 1
  -NCLUSTER:<num>  	Number of Clusters
	integer number
	Minimum: 2
	Default: 10