Skip to main content

Clustering Model Predictor

Description​

Clustering is used to group all similar properties to N groups.

Properties​

Input​

  • Algorithm Type – Select the classification algorithm for model creation. The value can be “KMeans”. k-means algorithm searches for a pre-determined number of clusters within an unlabelled multidimensional dataset.
  • Input Data – Data for predicting values.
  • Model Name – Generated model name for prediction.

Misc​

  • DisplayName – Add a display name to your activity.
  • Private – By default, activity will log the values of your properties inside your workflow. If private is selected, then it stops logging.

Output​

  • Result – Prediction value returned by the specified model.