implementing and comparing various model fitting and classification techniques. Demonstrates Multivariate Gaussian, Bag-of-Words, Naïve Bayes, LDA, and QDA models. Applied to Iris, SMS Spam Collection, and Phoneme datasets for practical classification tasks. parameter estimation, performance evaluation, feature selection using Mutual Information.
python machine-learning text-classification numpy naive-bayes jupyter-notebook pandas feature-selection classification bag-of-words pattern-recognition lda roc-curve spam-detection mutual-information gaussian-models statistical-modeling qda odel-fitting cikit-learn
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Updated
May 2, 2025 - Jupyter Notebook