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Linear_​Regression - Exercise

Run Linear Regression and assess using x-partitionerPart B Normalize, partition data Run the same flow as Part A, however, use a X-Partitioner to split the data. This will enable us to assess whether there is achance that we we lucky in our results, by using multiple training/test sets. Run Multiple Regression and Assess Performance - Part A Pre-completed steps to set up the data. The CSV reader pullsfrom this location:knime://knime.workflow/../_INPUT/WeeklySalesAtSize(FakeData).csv Pre completed Data Setup Apply the Regression Learner and Predictor Use the Numeric Scorer to understand how themodel is performing.(You can also denormalize the data) Quickly reminder of theLinear Correlation node Node 176 Data Setup CSV Reader Run Linear Regression and assess using x-partitionerPart B Normalize, partition data Run the same flow as Part A, however, use a X-Partitioner to split the data. This will enable us to assess whether there is achance that we we lucky in our results, by using multiple training/test sets. Run Multiple Regression and Assess Performance - Part A Pre-completed steps to set up the data. The CSV reader pullsfrom this location:knime://knime.workflow/../_INPUT/WeeklySalesAtSize(FakeData).csv Pre completed Data Setup Apply the Regression Learner and Predictor Use the Numeric Scorer to understand how themodel is performing.(You can also denormalize the data) Quickly reminder of theLinear Correlation node Node 176 Data Setup CSV Reader

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Created by: richardson.bg
Created at: 2017-05-15
On NodePit since: 2024-10-14
Last update: 2024-11-17
Created with KNIME version: v5.2.0

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