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04_​Parameter_​Optimization_​in_​Spark

Mix and match Spark nodes with other KNIME nodes
Mix and Match Parameter Optimization in Spark This workflow mixes standard KNIME nodes with the Spark nodes to find the optimal parameters for a k-means clustering using the hillclimbing approach. train model in Spark with k controlled by optimization loope.g. hillclimbinge.g. entropyKNIME tableto DataFrameCache DataFrameprior loopexecutiontraining datatest data Spark k-Means Parameter OptimizationLoop Start Spark MLlib to PMML Cluster Assigner ParameterOptimization Loop End Scoring Table to Spark Persist SparkDataFrame/RDD Create Local BigData Environment File Reader(Complex Format) File Reader(Complex Format) Mix and Match Parameter Optimization in Spark This workflow mixes standard KNIME nodes with the Spark nodes to find the optimal parameters for a k-means clustering using the hillclimbing approach. train model in Spark with k controlled by optimization loope.g. hillclimbinge.g. entropyKNIME tableto DataFrameCache DataFrameprior loopexecutiontraining datatest dataSpark k-Means Parameter OptimizationLoop Start Spark MLlib to PMML Cluster Assigner ParameterOptimization Loop End Scoring Table to Spark Persist SparkDataFrame/RDD Create Local BigData Environment File Reader(Complex Format) File Reader(Complex Format)

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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: koetter
Created at: 2015-05-27
On NodePit since: 2020-04-22
Last update: 2024-04-16
Created with KNIME version: v4.4.0
Tags: Parameter OptimizationGrid SearchHillclimbing

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