A method can include determining a cell of a grid to which a first feature and a second feature of each of a plurality of input/output examples maps, determining an average of respective features of the cell to generate respective level 2 synthetic feature vectors, for each cell with an input/output example of the input/output examples mapped thereto, generating a sub-grid of cells and map the input/output examples mapped to a cell of the sub-grid, determining an average of respective features to generate respective level 1 synthetic feature vectors comprising the average of the respective features, training the ML technique using the level 2 synthetic feature vector, testing the trained ML technique using the level 1 synthetic feature vector of each sub-cell, and further testing the trained ML technique using the input/output examples to generate a class and confidence for each of the input/output examples.