NodeVariable to Table Column

Other

Extracts variables that are carried along the flow and appends them to an input table.

External Resources

Input Ports

  1. Port Type: Flowvariable
    One or more flow variables (optional)
  2. Port Type: Data
    Data table to which the flow variables are appended as columns

Output Ports

  1. Port Type: Data
    The input table with additional columns, one for each selected variable. All values in the new column will be the same.

  1. Customer prediction with H2O in KNIME

    The purpose of this workflow is to showcase the ease of use of the H2O functionalities from within KNIME. As a real worl…
    shima0011 > 04_Analytics > 15_H2O_Machine_Learning > 07_Customer_prediction_with_H2O

  2. Variable Importance

    This workflow calculates how important each variable is for a correct classification.
    knime > Examples > 04_Analytics > 11_Optimization > 04_Meassuring_Variable_Importance

  3. Fault tolerant Workflow orchestration

    This example shows how to orchestrate the fault tolerant execution of multiple local KNIME Workflows. All Workflows in t…
    knime > Examples > 06_Control_Structures > 07_Workflow_Orchestration > 01_Fault_Tolerant_Workflow_Orchestration

  4. Network Traffic (PCAP) Reporting

    cybersecurity reporting IP IP address
    This workflow generates a report showing connection statistics of IP addresses of hosts in a computer network. The packa…
    knime > Examples > 50_Applications > 12_Network_Traffic_Reporting > 01_Network_Traffic_Reporting

  5. 02_Bioactivity_Prediction_Transform

    This workflow is the second one executed by the Model Factory. It removes artifacts and computes chemical fingerprints u…
    knime > Examples > 50_Applications > 37_Monster_Model_Factory > Process > _Process_Step_Templates > workflows > Templates > 02_Bioactivity_Prediction_Transform

  6. Simple Document Classification using Word Vectors

    deeplearning machine learning word2vec doc2vec word vectors embeddings classification
    This example shows how to transform a document into a vector using a word vector model and using these vectors for class…
    shima0011 > 04_Analytics > 14_Deep_Learning > 01_DL4J > 07_Simple_Document_Classification_Using_Word_Vectors

  7. Simple Document Classification using Word Vectors

    deeplearning machine learning word2vec doc2vec word vectors embeddings classification
    This example shows how to transform a document into a vector using a word vector model and using these vectors for class…
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 07_Simple_Document_Classification_Using_Word_Vectors

  8. Fun with Tags

    Automated access to disease information is an important goal of information extraction and text mining efforts. Here, we…
    knime > Examples > 08_Other_Analytics_Types > 02_Chemistry_and_Life_Sciences > 03_Fun_with_Tags

  9. The KNIME Model Factory

    model process model process factory enterprise
    This workflow is part of the model factory eco system. Please refer to our white paper for further details. This is the …
    knime > Examples > 50_Applications > 26_Model_Process_Management > 01_Model_Factory

  10. The KNIME Model Factory

    model process model process factory enterprise
    This workflow is part of the model factory eco system. Please refer to our white paper for further details. This is the …
    knime > Examples > 50_Applications > 26_Model_Process_Management > Factory > Model_Factory