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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

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Created by: Emilio Silvestri
Created at: 2019-11-29
On NodePit since: 2021-07-13
Last update: 2024-12-21
Created with KNIME version: v4.4.0
Tags: regressionmachine learningeducation

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