Icon

lft curve test w scorer

SVM on iris dataset

This workflow solves a classification problem on the iris dataset using Support Vector Machines (SVM).

Classification of the iris dataset using SVM Train SupportVector MachinePerform classificationon test data80% training20% testScore performanceNode 12Node 13Read DataRead to Applyto New DataRead Unlabeled DataRead ModelUse Model to LabelNew Data SVM Learner SVM Predictor Partitioning Scorer (JavaScript) ROC Curve Lift Chart Table Reader Model Writer CSV Reader Model Reader SVM Predictor Classification of the iris dataset using SVM Train SupportVector MachinePerform classificationon test data80% training20% testScore performanceNode 12Node 13Read DataRead to Applyto New DataRead Unlabeled DataRead ModelUse Model to LabelNew DataSVM Learner SVM Predictor Partitioning Scorer (JavaScript) ROC Curve Lift Chart Table Reader Model Writer CSV Reader Model Reader SVM Predictor

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: 2020-02-12
On NodePit since: 2023-11-28
Last update: 2024-04-27
Created with KNIME version: v4.7.7
Tags: TheGuideBookSVMclassificationSupport Vector MachineGIDS

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

Try NodePit Runner!