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Random Forest Example

Random Forest Model Deployment

Reads housing data with target of sales type. Illustrates how to deploy model to analyze a new data set employing the original model.

New Model. Reads model createdfrom training data and creates outputfrom new data. In a real situation thispart would be a new workflow with newdata, not data from the testing portionof the partition. 70/30Node 50Read modelproduced byLearnerRemoves SalePrice.Not needed w/ new datawith no SalePrice.Read Housing DataFeed new dataw/ appropriate FileReader to data port ofPredictor node.Node 60Node 61Node 62Node 63 Partitioning Model Writer Model Reader Column Filter Table Reader File Reader Random Forest Learner(Regression) Random Forest Predictor(Regression) Numeric Scorer Random Forest Predictor(Regression) New Model. Reads model createdfrom training data and creates outputfrom new data. In a real situation thispart would be a new workflow with newdata, not data from the testing portionof the partition. 70/30Node 50Read modelproduced byLearnerRemoves SalePrice.Not needed w/ new datawith no SalePrice.Read Housing DataFeed new dataw/ appropriate FileReader to data port ofPredictor node.Node 60Node 61Node 62Node 63Partitioning Model Writer Model Reader Column Filter Table Reader File Reader Random Forest Learner(Regression) Random Forest Predictor(Regression) Numeric Scorer Random Forest Predictor(Regression)

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: Emilio Silvestri
Created at: 2019-11-29
On NodePit since: 2023-09-08
Last update: 2026-01-10
Created with KNIME version: v4.7.7
Tags: regressionmachine learningeducation

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