Uses the MNIST dataset with 60,000 images of handwritten digits and 10,000 testing images. Goal of the project was to create a Naive Bayes classifier to match the images to their respective labels. After training I created three confusion matrices using the Seaborn package, these are included in the report PDF HERE.
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Image classification using naive bayes classifier model. Also uses PCA to reduce dimensionality. Project for Statistical Learning and Neural Networks Spring 2023
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