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4. Clustering and Regression

KBL: Clustering and Regression
Workflow: Clustering and Regression This workflow shows a few more data analysisalgorithms:- a linear regression to predict hte number of hours/week given all other attribute values- a k-Means clustering to group together the mostsimilar data rows. Remember that k-Means, like Neural Networks,needs normalized data.The Statistics node mainly produces generalstatstical measures about one data column,including a roughly drawn histogram. training_set.csv filewritten by workflowPrepare Dataassign new datato clusterstest_set.csv filewritten by workflowPrepare Datageneral statspredict hours/weekon all remaining attrsMin-max normalizationin [0,1]3 clusterswith Euclideandistancerun predictions from model CSV Reader Cluster Assigner CSV Reader Statistics Linear RegressionLearner Normalizer k-Means RegressionPredictor Workflow: Clustering and Regression This workflow shows a few more data analysisalgorithms:- a linear regression to predict hte number of hours/week given all other attribute values- a k-Means clustering to group together the mostsimilar data rows. Remember that k-Means, like Neural Networks,needs normalized data.The Statistics node mainly produces generalstatstical measures about one data column,including a roughly drawn histogram. training_set.csv filewritten by workflowPrepare Dataassign new datato clusterstest_set.csv filewritten by workflowPrepare Datageneral statspredict hours/weekon all remaining attrsMin-max normalizationin [0,1]3 clusterswith Euclideandistancerun predictions from modelCSV Reader Cluster Assigner CSV Reader Statistics Linear RegressionLearner Normalizer k-Means RegressionPredictor

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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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On NodePit since: 2021-06-07
Last update: 2024-04-27
Created with KNIME version: v4.3.1
Tags: KNIMEPressEducationk-meansClusteringLinear regressionNormalization

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