K-Means clustering help page
This is the page dedicated to help users of data mining web application in case of selection of Kmeans (Clustering_Kmeans) Model to make clustering experiments. This page is also directly reachable from the web application, in case users select the help button. The following contents are mainly dedicated to assist the user during the model parameter selection and setup, by giving details about each parameter, its role in the model, default value and suggestions about the right choice. There is one sub-section only (RUN case), related with the unique use case that users can select to perform experiments.
Functionality: Clustering with Kmeans model
Parameter specifications
Use Case: RUN
- Input Dataset
- Max number of iterations
- Number of clusters to search
- Output type
this parameter is a required field!
Input dataset file. WARNING: ONLY TABULAR DATA (NO IMAGES!)
number of training iterations.
If left empty, its default is 100
number of clusters to be searched during processing dataset.
If left empty, its default is 2
type of output to be generated at the end of processing.
If left empty, its default is csv
Copyright © 2010 DAME Collaboration. All right reserved.