Systems, methods, and apparatus to classify personalized data

A non-transitory computer readable medium comprising computer readable instructions that, when executed, cause at least one processor to at least:

• associate a data collector with a class by executing a classification model using a first data collector characteristic, the first data collector characteristic corresponding to the data collector, the classification model generated by applying a learning algorithm to classification training data, the classification training data including second data collector characteristics of a training group;
• select the class based on a requested characteristic of a task request from a distribution agent;
• select the data collector associated with the class;
• and
• transmit the selection to the distribution agent.

A method, comprising:

• associating, by executing an instruction with a processor, a data collector with a class by executing a classification model using a first data collector characteristic, the first data collector characteristic corresponding to the data collector, the classification model generated by applying a learning algorithm to classification training data, the classification training data including second data collector characteristics of a training group;
• in response to receiving a task request from a distribution agent, selecting, by executing an instruction with the processor, the class based on a requested characteristic of the task request;
• selecting, by executing an instruction with the processor, the data collector associated with the class;
• and
• sending, by executing an instruction with the processor, the selection to the distribution agent.