Tool Cluster Analysis (Table)
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: Table|Classification
Parameters
| Name | Type | Identifier | Description | Constraints |
Input | Table | Table, input | INPUT | - | - |
Output | Result (*) | Table, output, optional | RESULT | - | - |
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 | NCLUSTER | - | Minimum: 2 Default: 10 |
(*) optional |
Command-line
Usage: saga_cmd table_tools 28 [-INPUT <str>] [-RESULT <str>] [-FIELDS <str>] [-NORMALISE <str>] [-CLUSTER <str>] [-STATISTICS <str>] [-METHOD <str>] [-NCLUSTER <num>]
-INPUT:<str> Table
Table, input
-RESULT:<str> Result
Table, 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
Minimum: 2
Default: 10