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03_​Train_​MNIST_​classifier

KNIME Deep Learning - Train MNIST classifier

This workflow trains a simple convolutional neural network (CNN) on the MNIST dataset via Keras.

In order to run the example, please make sure you have the following KNIME extensions installed:

* KNIME Deep Learning - Keras Integration (Labs)
* KNIME Image Processing (Community Contributions Trusted)
* KNIME Image Processing - Deep Learning Extension (Community Contributions Trusted)

You also need a local Python installation that includes Keras. Please refer to https://www.knime.com/deeplearning#keras for installation recommendations and further information.

Acknowledgements:

The architecture of the created network was taken from https://github.com/fchollet/keras/blob/master/examples/mnist_cnn.py [1].

The enclosed pictures are from the MNIST dataset (http://yann.lecun.com/exdb/mnist/) [2].

[1] Chollet, Francois and others. Keras. https://github.com/fchollet/keras. 2015.

[2] Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. "Gradient-based learning applied to document recognition." Proceedings of the IEEE, 86(11):2278-2324, November 1998.

KNIME Deep Learning - Train MNIST classifier This workflow trains a simple convolutional neural network (CNN) on theMNIST dataset via Keras. MNIST imagesMNIST imagestransform probabilitiesto predicted classes’ labelsopenView: Confusion Matrixinput: trained netand test imagesoutput: probabilitiesof predicted digitssimple, untrainedCNNinput: untrained net andtraining images with labelsoutput: trained net- -5 epochs(increase to improve accuracy) Preparetraining data Prepare test data Format results Scorer Image Viewer DL Network Executor(deprecated) DL PythonNetwork Creator Keras NetworkLearner KNIME Deep Learning - Train MNIST classifier This workflow trains a simple convolutional neural network (CNN) on theMNIST dataset via Keras. MNIST imagesMNIST imagestransform probabilitiesto predicted classes’ labelsopenView: Confusion Matrixinput: trained netand test imagesoutput: probabilitiesof predicted digitssimple, untrainedCNNinput: untrained net andtraining images with labelsoutput: trained net- -5 epochs(increase to improve accuracy) Preparetraining data Prepare test data Format results Scorer Image Viewer DL Network Executor(deprecated) DL PythonNetwork Creator Keras NetworkLearner

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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: marcel
Created at: 2017-07-05
On NodePit since: 2024-08-07
Last update: 2024-12-17
Created with KNIME version: v4.1.0
Tags: deep learningKerasimage classification

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