http://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/

 

1) ID number 
2) Diagnosis (M = malignant, B = benign) 
3-32) 

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)

 

View that classify the dataset with the user chosen algorithm which may be the following:

​For the Neural network recieves the learning rate, regularization parameter, the number of perceptrons at the hidden layer and the number of iterations.

 

For the K-Nearest Neighboors recieves the number of neighboors to make the prediction and the distance function.