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Training_​a_​Housing_​Price_​Predictor_​AutoML

Example: Housing Price PredictionWe will predict the price of a house in Ames (Iowa, USA) given a number of selected numerical features:-The data set is partitioned into the training (70%) and testing (30%)sets-The linear regression model is trained on the training data set. Target: house price, features: all numerical features-The trained model is fitted to the testing data. -We evaluate the model performance Price Prediction: Linear Regression execute up-streambefore configurationhousing dataset AutoML (Regression) Partitioning Numeric Scorer CSV Reader Missing Value Workflow Executor Example: Housing Price PredictionWe will predict the price of a house in Ames (Iowa, USA) given a number of selected numerical features:-The data set is partitioned into the training (70%) and testing (30%)sets-The linear regression model is trained on the training data set. Target: house price, features: all numerical features-The trained model is fitted to the testing data. -We evaluate the model performance Price Prediction: Linear Regression execute up-streambefore configurationhousing dataset AutoML (Regression) Partitioning Numeric Scorer CSV Reader Missing Value Workflow Executor

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Created by: alinebessa
Created at: 2022-11-07
On NodePit since: 2022-11-08
Last update: 2024-04-26
Created with KNIME version: v4.6.3

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