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Simple_​neural_​network_​for_​binary_​classification

Simple Feed Forward Neural Network for Binary Classification

This workflow has been developed for the "friendly introduction to deep learning" webinar.

It shows a simple feed forward neural network with one hidden layer.

Read and preprocess the training and test data Train and apply model Extract prediction and evaluate trainednetwork Define the network structure CertificationresultsShape = 2Units: 2Activation: TanhUnits: 1 Activation: SigmoidEncode classPassed = 1Not Passed = 070% Top: Training30% Bottom: Verification and Test10% Top: Validation90% Bottom: TestOutput >=0.5 => PassedOutput <0.5 => Not PassedEpochs: 120Loss: Binary CrossEntropy CSV Reader Keras Input Layer Keras Dense Layer Keras Dense Layer Rule Engine Partitioning Partitioning Normalizer Normalizer (Apply) Rule Engine Keras NetworkLearner Scorer Keras NetworkExecutor Read and preprocess the training and test data Train and apply model Extract prediction and evaluate trainednetwork Define the network structure CertificationresultsShape = 2Units: 2Activation: TanhUnits: 1 Activation: SigmoidEncode classPassed = 1Not Passed = 070% Top: Training30% Bottom: Verification and Test10% Top: Validation90% Bottom: TestOutput >=0.5 => PassedOutput <0.5 => Not PassedEpochs: 120Loss: Binary CrossEntropy CSV Reader Keras Input Layer Keras Dense Layer Keras Dense Layer Rule Engine Partitioning Partitioning Normalizer Normalizer (Apply) Rule Engine Keras NetworkLearner Scorer Keras NetworkExecutor

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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: kathrinmelcher
Created at: 2021-02-26
On NodePit since: 2021-03-08
Last update: 2024-12-17
Created with KNIME version: v4.3.1

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