/ML-Algorithms-for-Breast-Cancer-Prediction

Application of several machine learning techniques to classify whether the tumor mass is benign or malignant in women residing in the state of Wisconsin, USA.

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ML-Algorithms-for-Breast-Cancer-Prediction

INTRODUCTION

Breast cancer is a malignant cell growth in the breast. If left untreated, the cancer spreads to other areas of the body. Excluding skin cancer, breast cancer is the most common type of cancer in women in the United States, accounting for one of every three cancer diagnoses. Breast cancer ranks second among cancer deaths in women.

AIM

The goal of this notebook is the application of several machine learning techniques to classify whether the tumor mass is benign or malignant in women residing in the state of Wisconsin, USA. This will help in understanding the important underlaying importance of attributes thereby helping in predicting the stage of breast cancer depending on the values of these attributes.

METHODS

  1. Principal Component Analysis
  2. K Nearest Neighbours
  3. Gaussian Naive Bayes
  4. Logistic Regression
  5. Random Forest
  6. XGBoost
  7. SVM
  8. Stacking