Predicting-Breast-Cancer

Logistic Regression Model has been used to predict the chances of Breast Cancer.

About Dataset

Attribute Information:-

1. id
2. diagnosis: M = malignant, B = benign

Columns 3 to 32 Ten real-valued features are computed for each cell nucleus:

3. radius: distances from center to points on the perimeter
4. texture: standard deviation of gray-scale values
5. perimeter
6. area
7. smoothness: local variation in radius lengths
8. compactness: perimeter^2 / area - 1.0
9. concavity: severity of concave portions of the contour
10. concave points: number of concave portions of the contour
11. symmetry
12. fractal dimension: "coastline approximation" - 1 The mean, standard error, and "worst" or largest (mean of the three largest values) of these features were computed for each image, resulting in 30 features. For instance, field 3 is Mean Radius, field 13 is Radius SE, field 23 is Worst Radius.