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14_​Linear_​Regression_​with_​Spark

Linear Regression with Spark

This workflows trains and evaluates a linear regression model using spark.ml.

Reading the auto-MPG data, remove missing values, and partitioning into training /testing Linear regression model Create a localbig data envCreate aSpark DataFrame70 % Training30 % TestingRemovemissing HPRead auto-mpgTrain themodelApply trainedmodel to testdataEvaluate Create Local BigData Environment Table to Spark Spark Partitioning Missing Value Table Reader Spark LinearRegression Learner Spark Predictor(Regression) Spark NumericScorer Reading the auto-MPG data, remove missing values, and partitioning into training /testing Linear regression model Create a localbig data envCreate aSpark DataFrame70 % Training30 % TestingRemovemissing HPRead auto-mpgTrain themodelApply trainedmodel to testdataEvaluateCreate Local BigData Environment Table to Spark Spark Partitioning Missing Value Table Reader Spark LinearRegression Learner Spark Predictor(Regression) Spark NumericScorer

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: Satoru
Created at: 2020-07-22
On NodePit since: 2021-09-30
Last update: 2024-04-30
Created with KNIME version: v4.4.1
Tags: RegressionLinear RegressionSpark

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