anirudhev

// Spark : Train the model and save features, weights in PMML format
saveModelToS3(model.toPMML(),              // PMML string
              "miles_away_from_store",     // Feature names
              "trips_past_year",
              "rewards_card_holder",
              "lives_in_rural_area")

// Inside user-scoring microservice : Compute the user score
features = Map("miles_away_from_store" -> miles_away_from_store,
               "card_holder" -> card_holder,

anirudhev

log_it = -0.20 + 
         0.44*miles_away_from_store +
         0.14*trips_past_year +
         0.34*rewards_card_holder +
         0.35*lives_in_rural_area

and user_score = 1/(1+e^(-log_it))