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.