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optimize_​MLP

Multi Layer Perceptron

After the data is normalized and partitioned, Multi-Layer-Perzeptron (MLP) is trained and applied.

Optimize Multi Layer Perceptron Source: A simple example using a multi layer perceptron(MLP) learner andpredictor to classify some image data. For more information on the data set seehttps://archive.ics.uci.edu/ml/datasets/Statlog+(Landsat+Satellite)Forumpost: https://forum.knime.com/t/mlp-parameter-optimziation-loop/34887 normalize datasplit training setfrom test setuse neural networkto predict classesbuildneural networkNode 22Node 23Node 24Node 25 Normalizer(deprecated) Partitioning MultiLayerPerceptronPredictor RProp MLP Learner ParameterOptimization Loop End Parameter OptimizationLoop Start Scorer Table Reader Optimize Multi Layer Perceptron Source: A simple example using a multi layer perceptron(MLP) learner andpredictor to classify some image data. For more information on the data set seehttps://archive.ics.uci.edu/ml/datasets/Statlog+(Landsat+Satellite)Forumpost: https://forum.knime.com/t/mlp-parameter-optimziation-loop/34887 normalize datasplit training setfrom test setuse neural networkto predict classesbuildneural networkNode 22Node 23Node 24Node 25 Normalizer(deprecated) Partitioning MultiLayerPerceptronPredictor RProp MLP Learner ParameterOptimization Loop End Parameter OptimizationLoop Start Scorer Table Reader

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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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On NodePit since: 2021-07-28
Last update: 2024-04-27
Created with KNIME version: v4.4.0

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