Portable Format for Analytics

The Portable Format for Analytics (PFA) is a JSON-based predictive model interchange format conceived and developed by Jim Pivarski. PFA provides a way for analytic applications to describe and exchange predictive models produced by analytics and machine learning algorithms. It supports common models such as logistic regression and decision trees. Version 0.8 was published in 2015. Subsequent versions have been developed by the Data Mining Group.[1]

As a predictive model interchange format developed by the Data Mining Group, PFA is complementary to the DMG's XML-based standard called the Predictive Model Markup Language or PMML.[2]

Release history

VersionRelease date
Version 0.8.1November 2015

Data Mining Group

The Data Mining Group is a consortium managed by the Center for Computational Science Research, Inc., a nonprofit founded in 2008.[3]

Examples

  • reverse array:
 # reverse input array of doubles
 input: {"type": "array", "items": "double"}
 output: {"type": "array", "items": "double"}
 action:
   - let: { x : input}
   - let: { z : input}
   - let: { l : {a.len: [x]}}
   - let: { i : l}
   - while : { ">=" : [i,0]}
     do:
       - set : {z : {attr: z, path : [i] , to: {attr : x ,path : [ {"-":[{"-" : [l ,i]},1]}]  } } }
       - set : {i : {-:[i,1]}}
   - z
  • Bubblesort
 input: {"type": "array", "items": "double"}
 output: {"type": "array", "items": "double"}
 action:
   - let: { A : input}
   - let: { N : {a.len: [A]}}
   - let: { n : {-:[N,1]}}
   - let: { i : 0}
   - let: { s : 0.0}
   - while : { ">=" : [n,0]}
     do :
       - set : { i : 0 }
       - while : { "<=" : [i,{-:[n,1]}]}
         do :
           - if: {">": [ {attr: A, path : [i]} , {attr: A, path:[{+:[i,1]}]} ]}
             then : 
               - set : {s : { attr: A, path: [i]}}
               - set : {A : {attr: A, path : [i] , to: {attr: A, path:[{+:[i,1]}]} } }
               - set : {A : {attr: A, path : [{+:[i,1]}] , to: s }}
           - set : {i : {+:[i,1]}}
       - set : {n : {-:[n,1]}}                 
   - A


References

  1. "Data Mining Group". Retrieved December 14, 2017. The DMG is proud to host the working groups that develop the Predictive Model Markup Language (PMML) and the Portable Format for Analytics (PFA), two complementary standards that simplify the deployment of analytic models.
  2. "Portable Format for Analytics: moving models to production". Retrieved April 25, 2016.
  3. "2008 EO 990". Retrieved 16 Oct 2014.
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