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03_​LogisticRegression

Logistic Regression

Using the adult dataset, this workflow performs binary classification using a Logistic Regression. The target is the income column, either <=50K or <50K, predicted using the other anagraphc information. After partitioning the data into training set and test set, the logistic regression model is built on the training set and the performance is calculated on the test set using the Scorer node.

Binary classification problem, solved using a logistic regression model Handlemissing values80% training20% teststratified samplingPerformclassificationTrain LogisticRegressionClassificationperformanceRead theadult dataset Missing Value Partitioning Logistic RegressionPredictor LogisticRegression Learner Scorer (JavaScript) CSV Reader Binary classification problem, solved using a logistic regression model Handlemissing values80% training20% teststratified samplingPerformclassificationTrain LogisticRegressionClassificationperformanceRead theadult datasetMissing Value Partitioning Logistic RegressionPredictor LogisticRegression Learner Scorer (JavaScript) CSV Reader

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

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Created by: Emilio Silvestri
Created at: 2020-02-06
On NodePit since: 2024-04-10
Last update: 2024-05-01
Created with KNIME version: v4.7.3
Tags: TheGuideBookclassificationLogistic RegressionGIDS

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