Creating a K-means clustering model using ML Studio

Now, it's time for you to build a clustering model by yourself. ML Studio comes with two modules specific for K-means clustering.

The URL http://www.biz.uiowa.edu/faculty/jledolter/DataMining/protein.csv contains a dataset in CSV format.

It contains the protein intakes of 9 different food sources from 25 European countries. The first few instances in the dataset are listed as follows:

Let's build a clustering model to group the dataset into three clusters based on the protein intakes of different countries from a variety of sources.

Create a new experiment and drag the Reader module under the Data Input and Output section in the modules palette to the left of the canvas. On the properties pane to the right, choose Data Source as Web URL via HTTP, Data format as CSV, and tick the checkbox for CSV or TSV has header row. Also, on the URL textbox, add the previously mentioned URL to the CSV file.

Drag the K-Means Clustering module to the canvas...