Refined learning data representation for classifiers

An apparatus, comprising:

• a processor configured to execute one or more processes;
• and
• a memory configured to store a process executable by the processor, the process when executed operable to:
• initialize thresholds of a data representation of one or more data features, the thresholds specifying a first number of pre-defined bins;
• reciprocally merge adjacent bins of the pre-defined bins having substantially similar weights, the merging resulting in a second number of refined bins that is less than the first number;
• simultaneously learn weights of a linear decision rule associated with the one or more data features while merging;
• and
• establish a data-driven representation for a data-driven classifier based on the refined bins and learned weights.

A tangible, non-transitory, computer-readable media having software encoded thereon, the software when executed by a processor operable to:

• initialize thresholds of a data representation of one or more data features, the thresholds specifying a first number of pre-defined bins;
• reciprocally merge adjacent bins of the pre-defined bins having substantially similar weights, the merging resulting in a second number of refined bins that is less than the first number;
• simultaneously learn weights of a linear decision rule associated with the one or more data features while merging;
• and
• establish a data-driven representation for a data-driven classifier based on the refined bins and learned weights.