NodeCell To Model

Other

Converts a single table cell into a model output.

Input ports
  1. Input Table Type: Data
    Input Table
Output ports
  1. Output Model Type: PortObject
    Output Model
  1. Prediction_h2o_glm
    knime > Examples > 50_Applications > 36_Guided_Analytics_for_ML_Automation > 01_Guided_Analytics_for_ML_Automation > Prediction > Prediction_h2o_glm
  2. Guided Automation
    autoML guided analytics automated machine learning guided automation feature engineering parameter optimization hyperparameter hyper-parameter optimization feature selection WebPortal application web app machine learning
    This workflow generates a fully automated web based application to select, train, test, and optimize a number of machine…
    knime > Examples > 50_Applications > 36_Guided_Analytics_for_ML_Automation > 01_Guided_Analytics_for_ML_Automation > 01_Guided_Analytics_for_ML_Automation
  3. 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…
    knime > Examples > 04_Analytics > 15_H2O_Machine_Learning > 07_Customer_prediction_with_H2O
  4. Model Deployment as REST API
    Deployment REST JSON Model Prediction
    This workflow demontstrates a mode of deploying a model with KNIME. The workflow receives new unseen data via REST inter…
    ml4bwlquam > Public > 03_Model_Deployment_as_REST_API
  5. Wide and Deep Learning on the Census dataset
    deep learning wide learning tensorflow keras machine learning
    This workflow shows one way of applying deep learning to tabular data. The main focus of the workflow lies on data prepa…
    knime > Examples > 04_Analytics > 14_Deep_Learning > 02_Keras > 09_Wide_and_Deep_Learning_on_Census_Dataset
  6. Model Optimization and Selection
    This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementat…
    knime > Examples > 04_Analytics > 11_Optimization > 08_Model_Optimization_and_Selection
  7. Techniques for Dimensionality Reduction
    ETL big data data preprocessing performance accuracy classification dimensionality reduction LDA auto-encoder t-SNE PCA backward feature elimination forward feature selection feature selection
    This workflow performs classification on data sets that were reduced using the following dimensionality reduction techni…
    knime > Examples > 04_Analytics > 01_Preprocessing > 02_Techniques_for_Dimensionality_Reduction > 02_Techniques_for_Dimensionality_Reduction
  8. Model Deployment as REST API
    Deployment REST JSON Model Prediction Flight Delay
    This workflow demontstrates a mode of deploying a model with KNIME. The workflow receives new unseen data via a REST int…
    knime > Examples > 50_Applications > 27_Deployment_Options > 03_Model_Deployment_as_REST_API
  9. Model Deployment with Report and Email
    Deployment Model Prediction Report Email Flight Delay
    This workflow demontstrates two modes of deploying a model with KNIME. The workflow reads new unseen data from a file, s…
    afzal-gul > Public > 05_Model_Deployment_with_report_and_email
  10. Prediction_h2o_rndfor
    knime > Examples > 50_Applications > 36_Guided_Analytics_for_ML_Automation > 01_Guided_Analytics_for_ML_Automation > Prediction > Prediction_h2o_rndfor