NodeDL4J Feedforward Predictor (Regression)

Predictor

This node creates a regression prediction using the supplied network and test data. The node is intended to be used with the DL4J Feedforward Learner (Regression) node. The output is a column for each target feature containing the predicted value.

Input ports

  1. Deep Learning Model Type: DL4J Model
    Regression Deep Learning Model.
  2. Data Table Type: Data
    Data table containing testing data.

Output ports

  1. Data Table Type: Data
    Input data with prediction columns.

  1. Simple Regression of Simple Functions

    deeplearning machine learning regression mlp
    This workflow shows how to use an MLP for regression of simple functions.
    shima0011 > 04_Analytics > 14_Deep_Learning > 01_DL4J > 10_Simple_Regression_Of_Simple_Functions

  2. Housing Value Prediction using Regression

    deeplearning machine learning regression mlp
    This workflow shows how to use an MLP to predict a target value of a small real world example dataset.
    shima0011 > 04_Analytics > 14_Deep_Learning > 01_DL4J > 11_Housing_Value_Prediction_Using_Regression

  3. Housing Value Prediction using Regression

    deeplearning machine learning regression mlp
    This workflow shows how to use an MLP to predict a target value of a small real world example dataset.
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 11_Housing_Value_Prediction_Using_Regression

  4. Simple Regression of Simple Functions

    deeplearning machine learning regression mlp
    This workflow shows how to use an MLP for regression of simple functions.
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 10_Simple_Regression_Of_Simple_Functions