A Decision Table Example Model

RASON users have the ability to create and evaluate Decision Tables, starting with RASON V2019. A decision table contains a set of rules which specify actions to perform based on specific conditions. Decision tables are a good tool to use when there is a consistent number of rules, or conditions, to be evaluated followed by a specific set of actions to be performed once a rule, or condition, is met. For example, the simple decision table below returns a patient's medical risk rating based on their age and medical history.

{  
   modelName : "ExampleDT",
   modelType: "calculation",
   data: {
   age: { value: 54 }, medHistory: { value: 'good' }
   },
   decisionTables: {
      tblRisk: {
         inputs: ['age', 'medHistory'], outputs: ['riskRating', 'rule'],
         rules: [
            ['>60',	  'bad', 	'High',   'r2'],
            ['[25..60]', '-', 	'Medium', 'r3'],
            ['<25',    'good',  'Low',    'r4'],
         ],
         hitPolicy: 'Unique'
   }
  },
  formulas: {
   res: { formula: "tblRisk(,,age, medHistory)", finalValue: [] }
  }
}

The results, as for optimization, simulation and data science models, are returned in JSON. A 54-year old patient with a good medical history rates as "medium" for his/her medical risk rating. See the chapter Defining Decision Tables in RASON for more information on how to define a decision table using the RASON modeling language.

  { "status": {
  "code": 0,
  "id": "2590+productMixCSV2Example+2020-01-02-05-21-19-476102",
  "codeText": "Solver has completed the calculation." },
  "observations": { "res": { "value": [ ["Medium", "r3"] ] } }
  }