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02_​NeuralNetwork_​DeepLearning

<p>Classifying the iris dataset with ANN 4-8-3<br><br>This workflow trains a multiplayer Perceptron with 4-8-3 units in the layers, using Back-Propagation, to classify the Iris dataset.</p>

Chapter 9

Artificial Neural Network


Classification of the iris data set using an ANN with 4-8-3 units in the layers trained with Back-Propagation.

input layer 4 units
Keras Input Layer
extract prediction
Rule Engine
RMSProp 200 epochs
Keras Network Learner
evaluate network performance
Scorer
to [0,1]
Normalizer
read the iris dataset
Table Reader
75% for training 25 % for testing
Table Partitioner
create collection cell of indices
Columns to Collection
hidden layer8 unitsReLu act. function
Keras Dense Layer
apply normaliz. function
Normalizer (Apply)
apply trained network
Keras Network Executor
transformclass to index
Rule Engine
output layer3 unitsSoftmax act. function
Keras Dense Layer

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: 2026-09-16
Last update: 2026-09-18
Created with KNIME version: v5.12.0
Tags: The GuideBookBackPropagationPerceptronneural networksdeep learningGIDS

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