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Skin Cancer Image Classification using Transfer Learning

Image Pre-Processing and Partitioning Transfer Learning Training & Model Evaluation NotesThe following workflow uses transfer learning backed by a VGG16 achitecture with imagenet weights inorder to classify images from a skin cancer dataset into benign or malignant.Dataset link: https://www.kaggle.com/fanconic/skin-cancer-malignant-vs-benign Append classcolumnsResize to 224x224x3Normalize between 0..1Encoding Class80/20Import VGG16Train the model for 20 epochs (Adam) withloss function binary crossentropyEvaluate the modelAccuracy (91%)Apply the modelon new dataoutput >= 0.5 Malignantoutput < 0.5 BenignAppend classcolumnsEncoding ClassNormalize between 0..1Resize to 224x224x3Node 369 Rule Engine Image Reader Image Resizer Image Calculator Category To Number Partitioning DL PythonNetwork Creator DL PythonNetwork Editor Keras NetworkLearner Scorer Keras NetworkExecutor Rule Engine Image Reader Rule Engine Category To Number Image Calculator Image Resizer Keras NetworkWriter Image Pre-Processing and Partitioning Transfer Learning Training & Model Evaluation NotesThe following workflow uses transfer learning backed by a VGG16 achitecture with imagenet weights inorder to classify images from a skin cancer dataset into benign or malignant.Dataset link: https://www.kaggle.com/fanconic/skin-cancer-malignant-vs-benign Append classcolumnsResize to 224x224x3Normalize between 0..1Encoding Class80/20Import VGG16Train the model for 20 epochs (Adam) withloss function binary crossentropyEvaluate the modelAccuracy (91%)Apply the modelon new dataoutput >= 0.5 Malignantoutput < 0.5 BenignAppend classcolumnsEncoding ClassNormalize between 0..1Resize to 224x224x3Node 369 Rule Engine Image Reader Image Resizer Image Calculator Category To Number Partitioning DL PythonNetwork Creator DL PythonNetwork Editor Keras NetworkLearner Scorer Keras NetworkExecutor Rule Engine Image Reader Rule Engine Category To Number Image Calculator Image Resizer Keras NetworkWriter

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Created by: junhw
Created at: 2021-12-20
On NodePit since: 2022-01-15
Last update: 2024-05-01
Created with KNIME version: v4.5.0

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