**Breast-Cancer-Detection-using-Machine-Learning**

Here I used Machine Learning to Detect Breast Cancer

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

I performed EDA on the dataset to check for null values, outliers

I have used the following ML Algorithms:
1. Logistic Regression 
Accuracy Score:
Train Accuracy: 0.9868131868131869
Test Accuracy: 0.9736842105263158

Classification Report (Test):
              precision    recall  f1-score   support

           0       0.97      0.99      0.98        71
           1       0.98      0.95      0.96        43

    accuracy                           0.97       114
   macro avg       0.97      0.97      0.97       114
weighted avg       0.97      0.97      0.97       114


Confusion Matrix (Test):
[[70  1]
 [ 2 41]]

2. Random Forest Classifier
Accuracy Score:
Train Accuracy: 0.989010989010989
Test Accuracy: 0.956140350877193

Recall Score:
Train Recall: 0.9704142011834319
Test Recall: 0.9069767441860465

Confusion Matrix (Test):
[[70  1]
 [ 4 39]]