A method to select a good setting for the kNN algorithm when using it for breast cancer prognosis

Breast cancer is the world´s second most frequent type of cancer and in Japan it is the third most frequent one. The prognosis of its recurrence, after a first treatment, is very important to increase the survival rate of a patient. This work shows the application of the k-Nearest Neighbors (kNN) method to prognosis breast cancer and also proposes a method to select a good setting with the parameters that can be changed when using this classification method. Using our method with the Wisconsin´s breast cancer prognosis data, the kNN method has an average accuracy of 76%, a small standard deviation, and a small difference between its maximum and minimum values.