Breast Cancer Classififer

Introduction

Breast Cancer Classififer Model ( ML ) With Hyper Parameter Tuning 97% Accuracy With Random Forest Classifier

Click Here to view Jypyter Notebbok File : Breast Cancer Classifier

About Dataset

Attribute Information:

1. ID number
2. Diagnosis (M = malignant, B = benign)

Ten real-valued features are computed for each cell nucleus:

a) radius (mean of distances from center to points on the perimeter)

b) texture (standard deviation of gray-scale values)

c) perimeter

d) area

e) smoothness (local variation in radius lengths)

f) compactness (perimeter^2 / area - 1.0)

g) concavity (severity of concave portions of the contour)

h) concave points (number of concave portions of the contour)

i) symmetry

j) fractal dimension ("coastline approximation" - 1)

Technology

• Pandas | Numpy | Matplotlib | Seaborn | Scikit Learn

References

• Dataset : https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Diagnostic%29