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I created a shorter diabetes risk quiz based on a diabetes survey respondent result dataset. I created 4 models, XGBC, LGBMC, SVC, Random Forest Regression, to analyze the dataset.

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Data Science Project 1_Diabetes Survey Optimization.pdf
Data Science Project 1_Diabetes Survey Optimization.pdf
 
 
README.md
README.md
 
 
main.py
main.py
 
 

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Project 1 - Diabetes Survey Optimization

[EDA - Data Preprocessing - Modelling (LazyClassification)]

Project Overview:

  • Perform an EDA to understand the correlation between data
  • Eliminate parameters with low correlation with diabetes
  • Data preprocessing for modelling
  • Created 4 models (XGBC, LGBMC, SVC, Random Forest Regression) chosen by considering the result of LazyClassification
  • Optimize the model with hyperparameter tuning and increase the accuracy

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I created a shorter diabetes risk quiz based on a diabetes survey respondent result dataset. I created 4 models, XGBC, LGBMC, SVC, Random Forest Regression, to analyze the dataset.

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machine-learning optimization regression automl

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