Sold by: Persistent SystemsÂ
Deployed on AWS
Classifies fine-needle aspirates (FNA) of breast mass as benign or malignant
Overview
Breast cancer is the most common form of cancer and the second most common cause of cancer deaths among women. This model is trained on features that are computed from a digitized image of a fine needle aspirate (FNA) biopsy of a breast mass. They describe characteristics of the cell nuclei such as radius, texture, perimeter, smoothness, concavity, symmetry etc.This model is not intended for medical diagnostic purpose.
Highlights
- Binary classifier that classifies fine-needle aspirates (FNA) of breast mass as benign or malignant
Details
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Delivery method
Latest version
Deployed on AWS
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Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m4.xlarge Inference (Batch) Recommended | Model inference on the ml.m4.xlarge instance type, batch mode | $0.00 |
ml.m4.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m4.xlarge instance type, real-time mode | $0.00 |
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
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Version release notes
First version released to AWS ML Marketplace
Additional details
Inputs
- Summary
Download the Jupyter notebook in "Additional Resources" section and follow readme.txt provided.
- Input MIME type
- csv, text
See Input Summary
See Input Summary
Resources
Vendor resources
Support
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