The data contains measurements on cells in suspicious
lumps in women's breast
We are able detect if there is an anomaly in women’s breast suspicious lumps.
An anomaly detection library was created using 3rd party tools.
Ten real-valued features were computed for each cell nucleus:
- radius (mean of distances from center to points on the perimeter)
- texture (standard deviation of gray-scale values)
- smoothness (local variation in radius lengths)
- compactness (perimeter^2 / area - 1.0)
- concavity (severity of concave portions of the contour)
- concave points (number of concave portions of the contour)
- fractal dimension ("coastline approximation" - 1)
The references are available on request containing detailed descriptions of how these features were
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.