Icon

Breast Cancer Binary Classification

Training & Evaluation Convolutional Neural Network Pre-Processing NotesDataset link: https://www.kaggle.com/uciml/breast-cancer-wisconsin-data read filesfilter for missingvalues70-30shape: 30Train the model for 100 epochs (Adam) withloss function mean squared errorApply the modelon new dataoutput <=0.5 Malignantoutput >0.5 BenignEvaluate the modelAccuracy (93.5%)70-30diagnosischeck parameters ofmodel CSV Reader Missing Value Partitioning Keras Input Layer Keras NetworkLearner Keras NetworkExecutor Rule Engine Scorer Partitioning Keras Dense Layer Keras Dense Layer Keras Dense Layer Category To Number Keras Dropout Layer Keras Dropout Layer DL PythonNetwork Editor Keras BatchNormalization Layer Keras BatchNormalization Layer Training & Evaluation Convolutional Neural Network Pre-Processing NotesDataset link: https://www.kaggle.com/uciml/breast-cancer-wisconsin-data read filesfilter for missingvalues70-30shape: 30Train the model for 100 epochs (Adam) withloss function mean squared errorApply the modelon new dataoutput <=0.5 Malignantoutput >0.5 BenignEvaluate the modelAccuracy (93.5%)70-30diagnosischeck parameters ofmodel CSV Reader Missing Value Partitioning Keras Input Layer Keras NetworkLearner Keras NetworkExecutor Rule Engine Scorer Partitioning Keras Dense Layer Keras Dense Layer Keras Dense Layer Category To Number Keras Dropout Layer Keras Dropout Layer DL PythonNetwork Editor Keras BatchNormalization Layer Keras BatchNormalization Layer

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: MSF
Created at: 2022-01-14
On NodePit since: 2022-01-15
Last update: 2024-04-26
Created with KNIME version: v4.4.2

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

Try NodePit Runner!