abideen-olawuwo / breastcancer

A Breast Cancer Prediction Model

• Problem Definition

Build classification models to predict whether the cancer type is Malignant or Benign

• Data

The data was downloaded from kaggle[https://www.kaggle.com/datasets/yasserh/breast-cancer-dataset]

• Evaluation

The Evaluation metric is to get the best accuracy

• Features

The data Features include; radius_mean, texture_mean, perimeter_mean, area_mean, smoothness_mean, compactness_mean, concavity_mean, concave, points_mean, radius_worst, texture_worst, perimeter_worst area_worst, smoothness_worst, compactness_worst, concavity_worst, concave points_worst symmetry_worst, fractal_dimension_worst

• Modelling

The Model used are Random Forest Classifier (RFC), Logistic Regression, Linear SVC, Adaboost Classifier, Catboost, Xgboost, Decision Tree, Logistic Regression, Kneigbhor