NodeCluster Assigner

Predictor

This node assigns new data to an existing set of prototypes, which are obtained e.g. by a k-means clustering. Each data point is assigned to its nearest prototype.

Input ports

  1. Prototypes Type: PMML
    Prototype model
  2. Input Data Type: Data
    DataTable containing the input data that will be assigned to the prototypes

Output ports

  1. Assigned Data Type: Data
    Input data assigned to cluster prototypes

  1. Performing a k-Means clustering

    clustering k-Means machine learning data mining
    This workflow shows how to perform a clustering of the iris dataset using the k-Means node.
    aajaradata > 01_Performing_a_k-Means_Clustering

  2. Clustering the Social Community

    social media clustering sentiment analysis leadership
    This workflow clusters social media users based on their authority (leader) and hub (follower) score and on their sentim…
    knime > Examples > 50_Applications > 05_Social_Media_clustering > 01_Clustering_the_Social_Community

  3. Model Selection to predict Death Occurrences in Car Accidents

    This workflow trains a few data analytics models and automatically selects the best one to predict death in car accident…
    knime > Examples > 50_Applications > 21_Model_Selection_and_Management > 01_Model_Selection_Sampled

  4. Mix and Match Spark Nodes with other KNIME Nodes

    This workflow mixes standard KNIME nodes with the Spark nodes to find the optimal parameters for a k-means clustering us…
    knime > Examples > 10_Big_Data > 02_Spark_Executor > 04_Parameter_Optimization_in_Spark

  5. Performing a k-Means clustering

    clustering k-Means machine learning data mining
    This workflow shows how to perform a clustering of the iris dataset using the k-Means node.
    shima0011 > 04_Analytics > 03_Clustering > 01_Performing_a_k-Means_Clustering

  6. Performing a k-Means clustering

    clustering k-Means machine learning data mining
    This workflow shows how to perform a clustering of the iris dataset using the k-Means node.
    knime > Examples > 04_Analytics > 03_Clustering > 01_Performing_a_k-Means_Clustering