Developed by | Jim Pivarski Data Mining Group |
---|---|
Latest release | 0.8.1 November 10, 2015 |
Type of format | Predictive modelling |
Extended from | JSON |
Website | dmg |
The Portable Format for Analytics (PFA) is a JSON-based predictive model interchange format conceived and developed by Jim Pivarski.[ citation needed ] 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]
Version | Release date |
---|---|
Version 0.8.1 | November 2015 |
The Data Mining Group is a consortium managed by the Center for Computational Science Research, Inc., a nonprofit founded in 2008. [3]
# 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
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
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PFA or Pfa may refer to:
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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.