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A small project using a Naive Bayes classifier to predict audiological etiologies with the Audiology (Standardized) Data Set from UCI. This project explores feature importance and handles both known and unknown etiologies using basic ML.
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For many patients in an audiology clinic, it is unclear what disease or condition causes their hearing loss. This is apparent in the Audiology (Standardized) Data Set, available from: https://archive.ics.uci.edu/ml/datasets/Audiology+%28Standardized%29
- This code trains a model on patients with known etiologies with 80% accuracy, which is then applied to patients with unknown etiologies.
- Feature selection is calculated to determine the most important predictors of etiology.
