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How to Develop a Machine Learning Classifier with MATLAB

 Using features extracted from signals collected from an endoscopic fluorescence imaging system, use Statistics and Machine Learning Toolbox to develop a machine learning classifier to discriminate normal tissue from cancerous tissue. 

The Classification Learner app lets you perform common supervised learning tasks such as interactively exploring data, ranking and selecting features, specifying validation schemes, training and optimizing models, and assessing results. Generate the corresponding MATLAB® code, or export classification models for use in MATLAB or integration into deployed devices and applications.

Related Resources: 

- Machine Learning Onramp:

- Supervised Learning:

- Fluorescence Tracker App:

- “How To” Video Series for Biomedical and Pharmaceutical Applications:

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