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08 Parameter Optimization

Exercise for building a parameter optimization loop.

Optimize the number of trees in a Random Forest model with a parameter optimization loop.


Exercise: Parameter Optimization LoopOptimize the number of trees in a Random Forest model.1.1) Start with a Parameter Optimization Loop Start node. Create a parameter for the number of treeswith start value=50, end value=150, and increment=10. It is an integer.1.2) Overwrite the number of models setting in the Random Forest Learner (Regression) node with thisparameter1.3) Transform the numeric scoring metrics into flow variables. Use the Table Column to Variable node.1.4) End with a Parameter Optimization Loop End node. Use MAPE as the objective value. What is theoptimal number of trees? Read AB_NYC_2019dataPredict priceR2 and error metricsInteractiveData Cleaning CSV Reader Random Forest Learner(Regression) Random Forest Predictor(Regression) Numeric Scorer Partitioning Replace 0 price byneighborhood average Exercise: Parameter Optimization LoopOptimize the number of trees in a Random Forest model.1.1) Start with a Parameter Optimization Loop Start node. Create a parameter for the number of treeswith start value=50, end value=150, and increment=10. It is an integer.1.2) Overwrite the number of models setting in the Random Forest Learner (Regression) node with thisparameter1.3) Transform the numeric scoring metrics into flow variables. Use the Table Column to Variable node.1.4) End with a Parameter Optimization Loop End node. Use MAPE as the objective value. What is theoptimal number of trees? Read AB_NYC_2019dataPredict priceR2 and error metricsInteractiveData Cleaning CSV Reader Random Forest Learner(Regression) Random Forest Predictor(Regression) Numeric Scorer Partitioning Replace 0 price byneighborhood average

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Created by: Maarit Laukkanen
Created at: 2020-10-27
On NodePit since: 2023-09-25
Last update: 2024-04-27
Created with KNIME version: v4.5.0
Tags: parameter optimization

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