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.
pythonmachine-learningtext-classificationnumpynaive-bayesjupyter-notebookpandasfeature-selectionclassificationbag-of-wordspattern-recognitionldaroc-curvespam-detectionmutual-informationgaussian-modelsstatistical-modelingqdaodel-fittingcikit-learn
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May 2, 2025 - Jupyter Notebook