Icon

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

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: marcel
Created at: 2017-07-05
On NodePit since: 2019-07-12
Last update: 2024-04-26
Created with KNIME version: v4.1.0
Tags: deep learningKerasimage classification

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!