/Breast_Cancer_Prediction

Primary LanguageJupyter Notebook

Breast Cancer Prediction with Machine Learning Models

Goals

  • Predict Breast Cancer using 3 ML models (Logistic Regression, Naive Bayes, KNN)
  • Predict whether the breast cancer tumor is malignant or benign
  • Compare models based on accuracy test, ROC values, and Confusion matrix

Data


https://www.kaggle.com/uciml/breast-cancer-wisconsin-data

Tools

  • Jupyter Notebook
  • Python (Pandas, Matplotlib, Sklearn, Numpy libraries>

Steps

  • Data Visualization: graphed data to see patterns
  • Data Analysis: studied data neatly
  • Data Cleaning: removed useless features
  • ML models: Applied the models one by one
  • Trained models
  • Compared test accuracy

Research Poster as a STAR Scholar

STAR Poster