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08 Parameter Optimization

08 Parameter Optimization
Exercise: Parameter Optimization LoopOptimize the number of trees in a Random Forest model.1.1) Start with a Parameter Optimization Loop Start node. Create aparameter for the number of trees with start value=50, end value=150, andincrement=10. It is an integer.1.2) Overwrite the number of models setting in the Random Forest Learner(Regression) node with this parameter1.3) Transform the numeric scoring metrics into flow variables. Use theTable Column to Variable node.1.4) End with a Parameter Optimization Loop End node. Use MAPE as theobjective value. What is the optimal number of trees? 50 Trees Predict priceR2 and error metricscustom data InteractiveData Cleaning Random Forest Learner(Regression) Random Forest Predictor(Regression) Numeric Scorer Parameter OptimizationLoop Start ParameterOptimization Loop End Partitioning Replace 0 price byneighborhood average Table Columnto Variable CSV Reader Exercise: Parameter Optimization LoopOptimize the number of trees in a Random Forest model.1.1) Start with a Parameter Optimization Loop Start node. Create aparameter for the number of trees with start value=50, end value=150, andincrement=10. It is an integer.1.2) Overwrite the number of models setting in the Random Forest Learner(Regression) node with this parameter1.3) Transform the numeric scoring metrics into flow variables. Use theTable Column to Variable node.1.4) End with a Parameter Optimization Loop End node. Use MAPE as theobjective value. What is the optimal number of trees? 50 Trees Predict priceR2 and error metricscustom dataInteractiveData Cleaning Random Forest Learner(Regression) Random Forest Predictor(Regression) Numeric Scorer Parameter OptimizationLoop Start ParameterOptimization Loop End Partitioning Replace 0 price byneighborhood average Table Columnto Variable CSV Reader

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Created by: Maarit Laukkanen
Created at: 2020-10-27
On NodePit since: 2021-06-30
Last update: 2024-12-17
Created with KNIME version: v4.3.2
Tags: parameter optimization

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