Icon

02_​Regression_​Tree

Regression Tree

Introduction to Machine Learning Algorithms course - Session 2
Exercise 2
- Partition data into train and test set
- Train a Regression Tree model
- Apply the trainel model to the test set
- Handle missing values
- Evaluate the model performances with the Numeric Scorer



Regresion: price prediction Exercise: Regression TreeIn this exercise we will predict the price of an house in Ames (Iowa, USA) given a number of features: size, neighborhood, heating type, ..1) Add Partitioning node to File Reader output - Top port should have 70 % of the rows - Draw randomly such rows2) Add Simple Regression Tree Learner to top output port of Partitioning node - Select price column to be learned - Execute the node and open its decision tree view. Which column is used in the beginning of the tree?3) Add Simple Regression Tree Predictor - Predict test set (remaining 30% rows) by simply connecting the remaining unconnected output ports4) Remove Rows with missing values5) 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 CSV Reader Regresion: price prediction Exercise: Regression TreeIn this exercise we will predict the price of an house in Ames (Iowa, USA) given a number of features: size, neighborhood, heating type, ..1) Add Partitioning node to File Reader output - Top port should have 70 % of the rows - Draw randomly such rows2) Add Simple Regression Tree Learner to top output port of Partitioning node - Select price column to be learned - Execute the node and open its decision tree view. Which column is used in the beginning of the tree?3) Add Simple Regression Tree Predictor - Predict test set (remaining 30% rows) by simply connecting the remaining unconnected output ports4) Remove Rows with missing values5) 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 CSV Reader

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: 2021-07-13
Last update: 2024-11-04
Created with KNIME version: v4.4.0
Tags: regressionmachine learningeducation

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

Try NodePit Runner!