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01_​Linear_​Regression

Linear Regression

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

Regresion: price prediction Exercise: Linear RegressionIn this exercise we will predict the price of an house in Ames (Iowa, USA) given a number of features: size, neighborhood, heating...1) Add Partitioning node to File Reader output - Top port should have 70 % of the rows - Draw randomly such rows2) Add Linear Regression Learner to top output port of Partitioning node - Select price column to be learned - Execute the node and open its scatter plot view. Which column is most correlated to the price (column selection tab)?3) Add Regression Predictor - Predict test set (remaining 30% rows) by simply connecting the remaining unconnected output ports4) Remove rows with missing prediction5) Add Numeric Scorer to Regression Predictor Output - Reference Column: the column you learned - Predicted Column: the new column created by the predictor node housing dataset File Reader Regresion: price prediction Exercise: Linear RegressionIn this exercise we will predict the price of an house in Ames (Iowa, USA) given a number of features: size, neighborhood, heating...1) Add Partitioning node to File Reader output - Top port should have 70 % of the rows - Draw randomly such rows2) Add Linear Regression Learner to top output port of Partitioning node - Select price column to be learned - Execute the node and open its scatter plot view. Which column is most correlated to the price (column selection tab)?3) Add Regression Predictor - Predict test set (remaining 30% rows) by simply connecting the remaining unconnected output ports4) Remove rows with missing prediction5) Add Numeric Scorer to Regression Predictor Output - Reference Column: the column you learned - Predicted Column: the new column created by the predictor node housing dataset File Reader

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Created by: Emilio Silvestri
Created at: 2019-11-29
On NodePit since: 2021-07-13
Last update: 2026-01-13
Created with KNIME version: v4.4.0
Tags: linear regressionmachine learningpredictioneducation

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