Icon

Training_​a_​Housing_​Price_​Predictor

Linear Regression Example - Ames Housing Data
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 housing dataset Partitioning Numeric Scorer Linear RegressionLearner RegressionPredictor CSV Reader Missing Value 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 housing dataset Partitioning Numeric Scorer Linear RegressionLearner RegressionPredictor CSV Reader Missing Value

Nodes

Extensions

Links

Download

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

Download Workflow
Created by: Emilio Silvestri
Created at: 2019-11-29
On NodePit since: 2022-11-08
Last update: 2024-05-01
Created with KNIME version: v4.6.3
Tags: linear regressionmachine learningpredictioneducation

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!