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Clustering
K-means Customer segmentation Data mining Machine learning CI
+8
  1. Workflow
    Analyze Data by Training a k-Means Clustering on Location Data
    Cluster K-Means Algorithm
    +4
    In this workflow, we perform a Clustering task on location data where we have longitude and latitude information. We use the k-me…
    knime > Beginners Space > 04_Analyze > 03_Analyze_Clustering_location_data
    5
  2. Workflow
    Performing a k-Means clustering
    Clustering K-Means Machine learning
    +1
    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
    5
  3. Workflow
    Customer Segmentation
    Clustering K-Means Customer segmentation
    +7
    This workflow performs customer segmentation by means of k-Mean clustering. The second part of the workflow implements an interac…
    knime > Examples > 50_Applications > 24_Customer_Segmentation_Use_Case > 02_Customer_Segmentation_Use_Case
    5
  4. Workflow
    Clustering with k-Means
    Clustering K-Means Machine learning
    +3
    This workflow performs clustering of the iris dataset using k-Means. Two workflows: one to build the k-Means prototypes (top) and…
    knime > Academic Alliance > Guide to Intelligent Data Science > Example Workflows > Chapter7 > 02_kMeans
    4
  5. Workflow
    Topic Extraction
    Topic Extraction Clustering
    +5
    This workflow shows how to extract topics from text documents using the Topic Extractor node. It reads textual data from a table …
    knime > Examples > 08_Other_Analytics_Types > 01_Text_Processing > 17_TopicExtraction_with_the_ElbowMethod
    3
  6. Workflow
    GPT3 Component and workflow
    GPT3 Semantic Scholar Clustering
    +6
    Using the Semantic Scholar API to retrieve some articles and after performing clustering tasks, the GPT3 component for Informatio…
    dromerosm > Public > MEDIUM - GPT3 Component
    3
  7. Workflow
    Basic Customer Segmentation
    Clustering K-Means Customer segmentation
    +3
    This workflow implements a basic customer segmentation through a clustering procedure. No input is required from the business ana…
    knime > Examples > 50_Applications > 24_Customer_Segmentation_Use_Case > 01_Basic_Customer_Segmentation_Use_Case
    2
  8. Workflow
    Clustering Strings
    Clustering
    This workflow performs assigns clusters based on Hierarchical Clustering for one string column using Levenshtein distance.
    ipazin > Public > 2019_08_12_Clustering_Strings
    2
  9. Workflow
    Semi Supervised Clustering
    T-SNE Clustering Dimensionality Reduction
    +3
    Visualize a table with t-SNE and cluster using k-means and hierarchical clustering.
    aaron_hart > Public > supervised-clustering
    2
  10. Workflow
    Clustering with DBSCAN
    Clustering Machine learning Data mining
    +3
    This workflow performs clustering of the iris dataset using DBSCAN. Notice the Numeric Distances node to feed the DBSCAN node wit…
    knime > Academic Alliance > Guide to Intelligent Data Science > Example Workflows > Chapter7 > 03_DBSCAN
    2
  11. Workflow
    Basic Customer Segmentation
    Clustering K-Means Customer segmentation
    +1
    This workflow implements a basic customer segmentation through a clustering procedure. The data is of a telecommunication company…
    ashokharnal > Collection of Components and Workflows > Clustering > Basic Customer Segmentation Use Case with weka
    1
  12. Workflow
    Customer Segmentation
    Clustering K-Means Customer segmentation
    +6
    This workflow is used in the practical exercises of the "L3-PC KNIME Server: Productionizing and Collaboration" self-paced course…
    knime > Education > Self-Paced Courses > L3-PC KNIME Server Course - Productionizing and Collaboration > Customer Segmentation
    1
  13. Workflow
    Performing a k-Medoids clustering
    Clustering K-Medoids Machine learning
    +1
    This workflow shows how to perform a clustering of the iris dataset using the k-Medoids node.
    knime > Examples > 04_Analytics > 03_Clustering > 02_Performing_a_k-Medoids_Clustering
    1
  14. Workflow
    Hierarchical Clustering
    Clustering Machine learning Data mining
    +3
    This workflow clusters the iris dataset using Hierarchical Clustering
    jjmie > Public > 01_HierarchicalClustering
    1
  15. Workflow
    Adding cluster labels after k-Means clustering
    Clustering K-Means Machine learning
    +2
    This workflow demonstrates how to add defined cluster labels after k-Means clustering on only one column is performed. This is do…
    ipazin > Public > 2020_09_25_Adding_Cluster_Labels_k-Means_Custering
    1
  16. Workflow
    Hierarchical Clustering
    Clustering Machine learning Data mining
    +3
    This workflow clusters the iris dataset using Hierarchical Clustering
    knime > Academic Alliance > Guide to Intelligent Data Science > Example Workflows > Chapter7 > 01_HierarchicalClustering
    1
  17. Node / Visualizer
    Hierarchical Cluster View
    Analytics Mining Clustering
    This view takes a hierarchical cluster tree and the same input table, that has been used for the creating the clustering and visu…
    1
  18. Workflow
    KBL: Clustering and Regression
    KNIMEPress Education K-means
    +3
    Exercise on linear regression and k-means clustering.
    pvn > Public > libro1 > Chapter4 > 4. Clustering and Regression
    0
  19. Workflow
    Basic Customer Segmentation
    Clustering K-Means Customer segmentation
    +3
    This workflow implements a basic customer segmentation through a clustering procedure. No input is required from the business ana…
    alinebessa > Courses and Workshops > Norbert and Michael - Workshop > Customer_Segmentation > Customer_Segmentation
    0
  20. Workflow
    Implementation of Different Clustering Algorithms
    Clustering Machine learning Data mining
    +4
    This workflow clusters the iris dataset using Hierarchical Clustering, DBSCAN and k-means
    kathrin > University Lectures > Lecture HU Berlin (Clustering) > Clustering_Exercises > 01_Clustering_Algorithms_Exercise
    0