16. The apparatus of claim 15 further comprising: for each candidate response template, determining the conversion rate in accordance with equation [1]: Conversion ⁢ ⁢ Rate = Success ⁢ ⁢ Count Attempt ⁢ ⁢ Count [ 1 ] 
 Success Count=Σ a ( SC User +SC Group +SC All ) 
 Attempt Count=Σ a ( I User +I Group +I All ) 
 SC User =w a w U ∥conversions a,U (Ø)∥ 
 SC Group =w a w G Σ kϵx ∥conversions a,k (Ø)∥ 
 SC All =w a w A ∥conversions a,A (Ø)∥ 
 Attempt Count=Σ a ( I User +I Group +I All ) 
 I User =w a e U ∥impressions a,U (Ø)∥ 
 I Group =w a w G Σ kϵx ∥impressions a,k (Ø)∥ 
 I All =w a w A ∥impressions a,A (Ø)∥ wherein: w a is an activity weight; w U is a user weight of a user U associated with the structured data input, w G is a group weight of a group G that includes the user and is a subset of all users of the supervised learning processing system, and w A is a weight for all users A of the supervised learning processing system; conversion is a conversion associated with the response template for an activity a by a user the user U, the group G, or all users A; and impression is an impression associated with the response template for an activity a by a user the user U, the group G, or all users A.
15. The apparatus of claim 9 wherein the ranking criteria comprises a function of a conversion rate of each of the candidate response templates that distributes the highest conversion rate ranking among candidate response templates to allow the machine to learn about each of the candidate response templates.