1. A computer-readable storage medium having computer-executable instructions, which when executed perform steps, comprising: a) extracting features from a selected sample of a plurality of samples of digital ink training data, wherein the digital ink training data corresponds to digital ink representative of at least two different types of digital ink input, each of the plurality of samples belong to one of a plurality of classes having combined feature data, and each of the plurality of samples is associated with a label comprising a recognition value; b) processing a feature dataset of the selected sample into a recognition model by adjusting the combined feature data of the class to which the selected sample belongs and maintaining data representative of the features extracted from the selected sample in association with the recognition value associated with the selected sample; c) selecting another sample from the plurality of samples and repeating steps a) and b) until each sample of the plurality of samples has been processed; and d) providing a unified recognizer that recognizes an input item of one of the at least two different types of digital ink input without mode selection or recognition parameter input, the input item being recognized by extracting features of the input item and determining a matching class having combined feature data that best match features of the input item, and outputting a matching recognition value associated with the matching class.
1. A computer-readable storage medium having computer-executable instructions, which when executed perform steps, comprising: a) extracting features from a selected sample of a plurality of samples of digital ink training data, wherein the digital ink training data corresponds to digital ink representative of at least two different types of digital ink input, each of the plurality of samples belong to one of a plurality of classes having combined feature data, and each of the plurality of samples is associated with a label comprising a recognition value; b) processing a feature dataset of the selected sample into a recognition model by adjusting the combined feature data of the class to which the selected sample belongs and maintaining data representative of the features extracted from the selected sample in association with the recognition value associated with the selected sample; c) selecting another sample from the plurality of samples and repeating steps a) and b) until each sample of the plurality of samples has been processed; and d) providing a unified recognizer that recognizes an input item of one of the at least two different types of digital ink input without mode selection or recognition parameter input, the input item being recognized by extracting features of the input item and determining a matching class having combined feature data that best match features of the input item, and outputting a matching recognition value associated with the matching class. 4. The computer-readable storage medium of claim 1 wherein determining the matching class comprises a multi-dimensional nearest neighbor search.