/immunization

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Immunization Logistic Regression

Contents

  1. immune_lr.ipynb: Python notebook containing data cleaning/preprocessing/modeling
  2. codeWithOutput.htm: HTML version of Python notebook containing data cleaning/preprocessing/modeling with output
  3. immune_data.csv: Csv file used to create model. 1085 records
  4. pneumo.csv: immunization probabilities for Pneumococcal vaccine 3/16-3/17
  5. tdap.csv: immunization probabilities for tdap vaccine 3/16-3/17
  6. metrics: output of training and testing performance for both pneumo and tdap models

Methodology

The vaccination probabilities found in each table was created by concatenating both training and testing results from each respective logistic regression model (1 model for predicting tdap vaccine 3/16-317, 1 model for predicting pneumo vaccine 3/16-3/17