performed by the support vector machines, a diagnostic. This paper uses dimensionality reduction technique offered by Weka tool called WrapperSubsetEval on two benchmark cancer datasets of Wisconsin and Portuguese “Breast Cancer Digital Repository” (BCDR), on top four data mining algorithms available in literature. There is an utmost thirst for diagnosis of breast cancer through an automation system in everyday health applications. This MATLAB code can be extended to generate analysis reports for large data sets as well. First, I’ll briefly describe the dataset, which was obtained from 699 biopsies. The Breast Cancer Wisconsin (Diagnostic) Data Set.
#CANCER DATASET IN MATLAB 2012 SOFTWARE#
Breast cancer being at number two in causing the deaths among women is equally among the most curable type of cancer if diagnosed prior to time. The ratings and popularity of MATLAB software are on top. This first article will train a shallow neural network on the data to predict cancer malignancy using the Breast Cancer Wisconsin (Diagnostic) Data Set built into MATLAB. With the advancement in the technological age, the deadly diseases threatening human survival also increase at the same pace.