K-Means Clustering
The K-Means Clustering
tool is an implementation of the k-means clustering algorithm for object-based clustering.
Using the interface
It is accessed through:
GeoDMA >
Classification >
K-means Clustering
In the Input Parameters group:
-
Vector Layer: select the layer
containing data to be classified.
-
Number of Clusters: Defines the number of patterns (clusters or classes)
to find in the data.
-
Maximum of iterations: defines the maximum number of iterations
to perform if convergence is not achieved.
-
Input Entries (%): defines the percentage of the input objects to be used
in the training step to find the means.
In the Input Features group:
-
Select, in the Available Features group, the features to be used in the clustering proccess.
After selecting the desired features, click
to move the selected features to the Used Features group. To remove features from the Used Features
group, click
. To move ALL the features
from the Available Features group to the Used Features group, click
. And, to
move all the features from the Used Features to the Available Features group, click
.
In the end, the features in the group
Used Features will be used in the model.
In the Output group:
-
Repository: define the repository to save the classification. Click
to save into an
ESRI Shape File or
to save into a database. If you want to save in the same input layer, you don't need to select
a repository here. Just don't change the output layer name.
-
Layer Name: define the name of the layer where the classification data will be
saved. If you want to save in the same input layer, just don't change the name here. Otherwise,
set here the name of the new layer to be created.
-
CSV File (Optional): Define an output CSV file if you want to save in this format. Click
to select the output CSV file.
-
Click Run to perform the operation or Close
to close the interface.