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21_​Regression_​Model_​Evaluation - Solution

21_Regression_Model_Evaluation - Solution
Exercise Regression Model Evaluation1) Read data german-credit-scoring.csv2) Partition the data into a training set (75 %) and test set (25 %). Draw randomly.3) Train a linear regression model on the training set to predict the duration of a credit. Use all other columns for theprediction.4) Apply the model to the test set5) Evaluate the performance of the linear regression model with the Numeric Scorer node. Which proportion of the varianceof the credit duration does the model explain? How many months is the mean absolute error of the model? The proportion of the varianceexplained is represented by the R^2metric, here about 50 %.The mean absolute error metricreports the average error in months,here about 7 months.NOTE: due to random partitioning,these values might slightly change atevery execution Read datagerman-credit-scoring.csvTop: train set (75%)Bottom: test set (25%)Random samplingTrain the modelto predict credit durationApply the modelto the test setEvaluate modelperformance File Reader Partitioning Linear RegressionLearner RegressionPredictor Numeric Scorer Exercise Regression Model Evaluation1) Read data german-credit-scoring.csv2) Partition the data into a training set (75 %) and test set (25 %). Draw randomly.3) Train a linear regression model on the training set to predict the duration of a credit. Use all other columns for theprediction.4) Apply the model to the test set5) Evaluate the performance of the linear regression model with the Numeric Scorer node. Which proportion of the varianceof the credit duration does the model explain? How many months is the mean absolute error of the model? The proportion of the varianceexplained is represented by the R^2metric, here about 50 %.The mean absolute error metricreports the average error in months,here about 7 months.NOTE: due to random partitioning,these values might slightly change atevery execution Read datagerman-credit-scoring.csvTop: train set (75%)Bottom: test set (25%)Random samplingTrain the modelto predict credit durationApply the modelto the test setEvaluate modelperformanceFile Reader Partitioning Linear RegressionLearner RegressionPredictor Numeric Scorer

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Created by: Maarit Laukkanen
Created at: 2020-04-20
On NodePit since: 2021-03-30
Last update: 2024-11-21
Created with KNIME version: v4.1.3
Tags: e-learningmodel evaluationr-squarederror metriceducation

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