scorecard 0.3
PMML Scorecard generator

pyscorecard
===========

Python client for submitting PMML ScoreCard models and queries against
them to OpenScoring

PMML ScoreCards: http://dmg.org/pmml/v4-2-1/Scorecard.html for
additional background

OpenScoring REST API: https://github.com/jpmml/openscoring Demo
instance: http://openscoring-ncoghlan.rhcloud.com/openscoring/ Demo git
repo: https://github.com/ncoghlan/openscoring-openshift

PMML ScoreCard generation from JSON input
-----------------------------------------

Command line invocation:

::

    pyscorecard input_spec.json pmml_output_dir

Output PMML file names are generated based on a combination of
"model\_name" and "param\_grid" entries as described below.

In the Python API, ``scorecard.pmml_scorecard`` generates PMML scorecard
definitions from a JSON-compatible input mapping.

See examples/risk\_example.json (input) and examples/risk\_example.xml
(output)

All ScoreCards produce a single predicted risk score and up to 3 reason
codes:

-  ``RiskScore``
-  ``ReasonCode1``
-  ``ReasonCode2``
-  ``ReasonCode3``

Generated ScoreCards are also currently all hardcoded to use the
"pointsAbove" reason code algorithm, the "min" baseline score algorithm,
``0`` as the initial score for the overall scorecard evaluation and
``1`` as the baseline score for each individual characteristic (this
ensures that characteristics achieving a partial score of ``0`` are
never reported as reason codes for the overall risk scoring).

The input format is a JSON mapping with the following fields:

-  ``model_name``: name of the model (also used as output filename
   prefix)
-  ``param_grid``: parameter definitions for use in characteristic
   predicates

-  key is the variable name that can be substituted into predicates
-  value is a mapping of output filename suffixes to substition values
-  when multiple grid parameters are defined, keys are lexically sorted
   when determining the combined output filename

-  ``data_fields``: sequence of field definitions for the DataDictionary
   and MiningSchema sections in the generated PMML Scorecard

-  ``name``: used in both the DataField entry and the MiningField entry
-  ``dataType``: used in the DataField entry
-  ``optype``: used in the DataField entry to define handling of
   comparisons
-  ``values``: permitted values for categorical and ordinal fields

-  ``characteristics``: sequence of definitions for the Characteristic
   section in the generated PMML Scorecard

-  ``name``: data field used by this characteristic. Also used to derive
   the characteristic name as ``name + "Score"`` and the overall
   characteristic reason code as ``name + "RC"``
-  ``attributes``: sequence of attribute definitions used by the
   characteristic

   -  ``reasonCode``: specific reason code when this criterion is met
   -  ``partialScore``: contribution to the risk score when this
      criterion is met
   -  ``predicate``: predicate defining this criterion (see below for
      details)

Predicates can be defined as either a single string, or as a sequence of
such strings. Each string predicate is of the form "OP value", with the
data field named in the characteristic definition being the implied left
hand side of the operation. Predicate sequences are implicitly and'ed
together to define the overall criterion to be met for that attribute.
Predicate values may start with ``$`` to indicate a grid parameter -
these will be substituted with the appropriate value for the scorecard
currently being generated.

Permitted operations are ``==`` for data fields with the ``categorical``
optype, and ``==``, ``<``, ``<=``, ``>=``, and ``>`` for data fields
with the ``ordinal`` or ``continuous`` optype.