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In this challenge, I try to predict the survival of hepatitis patients based on a collection clinical parameters. Multiple features, transformations and models are tried to find the best performing combination.

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nmirabets/hepatitis-challenge

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hepatitis-challenge

  • The project’s objective is to predict whether the patients will live or die based on multiple clinical parameters such as alk phosphate or bilirubin levels. The project is divided into two steps:
  1. Preprocessing: EDA, data cleaning and imputation of missing values using KNN
  2. Modelling: Data scaling and balancing, model tuning of RandomForestClassfier using GridSearchCV with Kappa as the scoring metric.

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In this challenge, I try to predict the survival of hepatitis patients based on a collection clinical parameters. Multiple features, transformations and models are tried to find the best performing combination.

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