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Prediction Using Linear Regression Models of Least Squares, Ridge Regression, and Lasso Regression

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TyrelM10/Predicting-Cancer-Antigen-Levels

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Predicting Cancer Antigen Levels.


  1. Data Preparation: I carefully imported and prepared clinical data for analysis, ensuring its quality and consistency.

  2. Regression Modelling and Model Selection: Using techniques like Least Squares, Ridge Regression, and Lasso Regression, I developed various linear regression models. By employing cross-validation methods, I determined the most effective model for predicting cancer antigen levels.

  3. Clinical Insights: I pinpointed and explained the most significant clinical measures influencing cancer antigen levels. These findings offer valuable insights for future research and potential medical applications.


This project boosted my skills in data preprocessing, regression modelling, and extracting meaningful insights from clinical data.

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Prediction Using Linear Regression Models of Least Squares, Ridge Regression, and Lasso Regression

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