BreastCancer

class openschema.sklearn.BreastCancer

Breast cancer Wisconsin (diagnostic) dataset.

Number of Instances:

569

Number of Attributes:

30 numeric, predictive attributes and the class

Attribute Information:

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.

Summary Statistics:

Feature

Min

Max

radius (mean):

6.981

28.11

texture (mean):

9.71

39.28

perimeter (mean):

43.79

188.5

area (mean):

143.5

2501.0

smoothness (mean):

0.053

0.163

compactness (mean):

0.019

0.345

concavity (mean):

0.0

0.427

concave points (mean):

0.0

0.201

symmetry (mean):

0.106

0.304

fractal dimension (mean):

0.05

0.097

radius (standard error):

0.112

2.873

texture (standard error):

0.36

4.885

perimeter (standard error):

0.757

21.98

area (standard error):

6.802

542.2

smoothness (standard error):

0.002

0.031

compactness (standard error):

0.002

0.135

concavity (standard error):

0.0

0.396

concave points (standard error):

0.0

0.053

symmetry (standard error):

0.008

0.079

fractal dimension (standard error):

0.001

0.03

radius (worst):

7.93

36.04

texture (worst):

12.02

49.54

perimeter (worst):

50.41

251.2

area (worst):

185.2

4254.0

smoothness (worst):

0.071

0.223

compactness (worst):

0.027

1.058

concavity (worst):

0.0

1.252

concave points (worst):

0.0

0.291

symmetry (worst):

0.156

0.664

fractal dimension (worst):

0.055

0.208

Missing Attribute Values:

None

Class Distribution:

212 - Malignant, 357 - Benign

Creator:

Dr. William H. Wolberg, W. Nick Street, Olvi L. Mangasarian

Donor:

Nick Street

Date:

November, 1995

See also

Original Sklearn documentation and the original UCIML dataset.

mean_radius: Real

Mean of distances from center to points on the perimeter (mean).

mean_texture: Real

Standard deviation of gray-scale values (mean).

mean_perimeter: Real

Perimeter (mean).

mean_area: Real

Area (mean).

mean_smoothness: Real

Local variation in radius lengths (mean).

mean_compactness: Real

perimeter^2 / area - 1.0 (mean).

mean_concavity: Real

Severity of concave portions of the contour (mean).

mean_concave_points: Real

Number of concave portions of the contour (mean).

mean_symmetry: Real

Symmetry (mean).

mean_fractal_dimension: Real

Coastline approximation - 1 (mean).

radius_error: Real

Mean of distances from center to points on the perimeter (standard error).

texture_error: Real

Standard deviation of gray-scale values (standard error).

perimeter_error: Real

Perimeter (standard error).

area_error: Real

Area (standard error).

smoothness_error: Real

Local variation in radius lengths (standard error).

compactness_error: Real

perimeter^2 / area - 1.0 (standard error).

concavity_error: Real

Severity of concave portions of the contour (standard error).

concave_points_error: Real

Number of concave portions of the contour (standard error).

symmetry_error: Real

Symmetry (standard error).

fractal_dimension_error: Real

coastline approximation - 1 (standard error).

worst_radius: Real

Mean of distances from center to points on the perimeter (worst).

worst_texture: Real

Standard deviation of gray-scale values (worst).

worst_perimeter: Real

Perimeter (worst).

worst_area: Real

Area (worst).

worst_smoothness: Real

Local variation in radius lengths (worst).

worst_compactness: Real

perimeter^2 / area - 1.0 (worst).

worst_concavity: Real

Severity of concave portions of the contour (worst).

worst_concave_points: Real

Number of concave portions of the contour (worst).

worst_symmetry: Real

Symmetry (worst).

worst_fractal_dimension: Real

coastline approximation - 1 (worst).

diagnosis: str

Diagnosis class.

Values:
  • M = malignant

  • B = benign