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02_​NeuralNetwork_​DeepLearning

Classifying the iris dataser with ANN 4-3-1

This workflow trains a multiplayer Perceptron with 4-8-3 layers, using BackPropagation, to classify the Iris dataset.

Classification of the iris data set using an ANN 4-8-3trained with BP read theiris datasetRMSProp200 epochsapplynormaliz.functionapply trained network75% for training 25 % for testinghidden layer 8 unitsReLu act. functionoutput layer3 unitsoftmax act. functionto [0,1]input layer 4 unitstransformclass to indexcreate collection cell of indicesextract predictionevaluate network performanceTable Reader Keras NetworkLearner Normalizer (Apply) Keras NetworkExecutor Partitioning Keras Dense Layer Keras Dense Layer Normalizer Keras Input Layer Rule Engine Create CollectionColumn Rule Engine Scorer Classification of the iris data set using an ANN 4-8-3trained with BP read theiris datasetRMSProp200 epochsapplynormaliz.functionapply trained network75% for training 25 % for testinghidden layer8 unitsReLu act. functionoutput layer3 unitsoftmax act. functionto [0,1]input layer 4 unitstransformclass to indexcreate collection cell of indicesextract predictionevaluate network performanceTable Reader Keras NetworkLearner Normalizer (Apply) Keras NetworkExecutor Partitioning Keras Dense Layer Keras Dense Layer Normalizer Keras Input Layer Rule Engine Create CollectionColumn Rule Engine Scorer

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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: 2020-02-12
On NodePit since: 2024-05-19
Last update: 2024-11-21
Created with KNIME version: v4.7.3
Tags: The GuideBookBackPropagationPerceptronneural networksdeep learningGIDS

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