A system that facilitates analyzing handwriting, comprising: an interface component that receives at least one handwritten character; and a personalization component that comprises: a classifier component comprising: an allograph neural network classifier trained using allograph data including a plurality of distinct handwriting styles for each character to map character feature vectors obtained from the received at least one handwritten character to character allographs; and a base neural network classifier trained to directly map the character feature vectors to output classes, wherein the classes correspond to different characters, wherein the allograph neural network classifier and the base neural network classifier have disparate architectures; and a combine component that combines outputs from the allograph neural network classifier and the base neural network classifier to provide handwriting recognition for the at least one handwritten character. an interface component that receives at least one handwritten character; and a personalization component that comprises: a classifier component comprising: an allograph neural network classifier trained using allograph data including a plurality of distinct handwriting styles for each character to map character feature vectors obtained from the received at least one handwritten character to character allographs; and a base neural network classifier trained to directly map the character feature vectors to output classes, wherein the classes correspond to different characters, wherein the allograph neural network classifier and the base neural network classifier have disparate architectures; and a combine component that combines outputs from the allograph neural network classifier and the base neural network classifier to provide handwriting recognition for the at least one handwritten character. a classifier component comprising: an allograph neural network classifier trained using allograph data including a plurality of distinct handwriting styles for each character to map character feature vectors obtained from the received at least one handwritten character to character allographs; and a base neural network classifier trained to directly map the character feature vectors to output classes, wherein the classes correspond to different characters, wherein the allograph neural network classifier and the base neural network classifier have disparate architectures; and an allograph neural network classifier trained using allograph data including a plurality of distinct handwriting styles for each character to map character feature vectors obtained from the received at least one handwritten character to character allographs; and a base neural network classifier trained to directly map the character feature vectors to output classes, wherein the classes correspond to different characters, wherein the allograph neural network classifier and the base neural network classifier have disparate architectures; and a combine component that combines outputs from the allograph neural network classifier and the base neural network classifier to provide handwriting recognition for the at least one handwritten character. <EOS>