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Ames housing regression tree

Linear Regression - solution

Introduction to Machine Learning Algorithms course - Session 2
Solution to exercise 1
- Partition data into training and test set
- Train a linear regression model
- Apply the trained model to the test set
- Handle missing values
- Evaluate the model performance with the Numeric Scorer node


Housing Price Prediction with a Regression Tree ModelIn this example we will predict the price of a house in Ames (Iowa, USA) given a number of features: size & quality1. Loading the data with the CSV reader node2. Remove numeric outliers3. Paritioning the data into the training (70%) & testing (30%) partitions4. Train a regression tree model with the SImple Regression Tree Learner node5. Generate predictions with the Simple Regression Tree Predictor node6. Assess the model performance with the Numeric Scorer node housing datasetOutliers areremovedAssessingthe quality ofthe modelTraining - 70%Testing - 30%Training aregression treemodelNode 75 CSV Reader Numeric Outliers Numeric Scorer Partitioning Simple RegressionTree Learner Simple RegressionTree Predictor Housing Price Prediction with a Regression Tree ModelIn this example we will predict the price of a house in Ames (Iowa, USA) given a number of features: size & quality1. Loading the data with the CSV reader node2. Remove numeric outliers3. Paritioning the data into the training (70%) & testing (30%) partitions4. Train a regression tree model with the SImple Regression Tree Learner node5. Generate predictions with the Simple Regression Tree Predictor node6. Assess the model performance with the Numeric Scorer node housing datasetOutliers areremovedAssessingthe quality ofthe modelTraining - 70%Testing - 30%Training aregression treemodelNode 75 CSV Reader Numeric Outliers Numeric Scorer Partitioning Simple RegressionTree Learner Simple RegressionTree Predictor

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Created by: Emilio Silvestri
Created at: 2019-11-29
On NodePit since: 2022-12-10
Last update: 2024-04-30
Created with KNIME version: v4.6.3
Tags: linear regressionmachine learningpredictioneducation

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