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Basic_​Example_​Iris_​Dataset

Simple Example for Multiclass Classification with Keras

This workflow trains a fully connected feedforward neural network with 4-8-3 units per layers to classify iris flowers.

Define network strucuture and train the network

Read and preprocess iris data
Apply trained network and extract predictions
z-score
Normalizer
reading the iris dataset
Table Reader
extract prediction
Rule Engine
evaluate network performance
Scorer
apply normaliz. function
Normalizer (Apply)
create collection cell of indices
Create Collection Column
RMSProp50 epochs
Keras Network Learner
transformclass to index
Rule Engine
input layer 4 units
Keras Input Layer
apply trained network
Keras Network Executor
output layer3 unitssoftmax
Keras Dense Layer
hidden layer8 unitsReLU
Keras Dense Layer
75% for training 25 % for testing
Partitioning

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: 2020-12-17
Last update: 2026-11-10
Created with KNIME version: v5.4.2
Tags: Perceptronneural networksdeep learning

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