Abstract: A method for generating descriptions of classification results, comprising classifying original inputs in a data set using a classifier. For one or more of the plurality of original inputs, apply an adjustment to one or more features of the original input to produce a respective adjusted input, and classify the respective adjusted input using the classifier. For one or more of the adjusted inputs, record a corresponding original input into a training set, and record information associated with the adjusted input into the training set. The method further comprises training a model based on the training set, such that the model is configured to receive an original model input and identify a hypothetical adjustment that would produce an adjusted model input that would be assigned an adjusted model classification with a different class than a class assigned to the original model input.

Abstract: Computer-implemented systems and methods for rendering a visual effect on a graphical element, including: generating an initial visual effect based on the graphical element; computing a mask shape based on the graphical element; generating a mask based on the mask shape from the graphical element; masking the initial visual effect based on the mask to generate a masked visual effect; and combining the masked visual effect with the graphical element into a combined graphical element and visual effect.

Abstract: Systems and methods for extracting parameters from invoice files are provided, including techniques to determine suppliers of invoice files using machine learning models. The system can identify an invoice file in a message, determine an analysis process, such as optical character recognition, for the invoice file based on the invoice file type, and perform an extraction process on the invoice file via a cloud computing system to extract objects from the invoice file. The system can extract invoice parameters from the objects using a first analysis process, and if the first analysis process fails to extract a predetermined set of invoice parameters, perform subsequent analysis processes to extract parameters that the first analysis process failed to extract. The system can then transmit the invoice parameters and the invoice file to a node server.