This data set has been generated using an experiment of stretching a collection of balloons carried out on a group of adults and children. In the data set, Inflated is true if (color=yellow and size = small) or (age=adult and act=stretch). In the data set there are two main output classes, namely T if inflated and F if not inflated, two colors yellow and purple, two sizes, large and small, two act types, stretch and dip, and two age groups, adult and child. After the pre processing step, the total number of input columns became 8.
Crime modus operandi dataset
This data set is composed of 48 columns. Each column represents whether that flow has taken place or not. The data set is composed of modus operandi of 20 criminals.
This data set has been generated to model psychological experimental results. Each example is classified as having the balance scale tip to the right, tip to the left, or be balanced. The attributes are the left weight, the left distance, the right weight, and the right distance. After the preprocessing step the number of input variables was changed to 20 binary values.
This data set has been created on a dermatology test carried out on skin samples which have been taken for the evaluation of 22 histopathological features. The values of the histopathological features have been determined by an analysis of the samples under a microscope. This data set has been moderated in such a way that it suits the proposed algorithm according to the Data preprocessing method proposed in the paper. Therefore, the processed data set has got 97 input variables and the class variable.