krishddd/cervicalcancer_risk_classification

Cervical Cancer Risk Factors for Biopsy:

Cervical_Cancer_Predection_with_ML

In this project, built and trained an XG-Boost classifier to predict whether a person has a risk of having cervical cancer. Data was obtained from 858 patients at 'Hospital Universitario de Caracas' in Caracas, Venezuels and included features such as number of pregnancies, smoking habits, Sexually Transmitted Disease (STD), demographics, and historic medical records. Performed Exploratory Data Analysis and Data Visualization on the training data set. Prepared the data and splitted into training and test dataset before Model Training. XG-Boost-Algorithm was trained and evaluated for this task using sci-kit library in Python. The Accuracy for this Machine Learning Model came out to be: -99.562 % (Training Dataset) -95.348 % (Test Dataset)

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