Decision Trees
Overview
Decision Trees are a powerful feature that allows for the automated routing and decision-making process based on predefined rules. This feature is especially useful in complex environments where various conditions need to be evaluated to determine the correct course of action, such as assigning prices, determining quantities, or routing documents.
Key Components
Decision Tree List: This is the main interface where all existing decision trees are listed. Each decision tree can be associated with a specific document type such as an
INVOICEorQUOTE.Decision Tree Designer: This interface allows for the creation and editing of decision trees, where you can define rules, operators, and actions to be taken when certain conditions are met.
Decision Tree Interface
Decision Tree List
The Decision Tree list displays all the available decision trees. Each entry shows:
Name: The name of the decision tree.
Document Type: The type of document associated with the decision tree (e.g.,
INVOICE,QUOTE).
Decision Tree Designer
The Decision Tree Designer allows you to configure rules that govern how decisions are made.
Components of the Decision Tree Designer
Rules: Each rule consists of conditions and actions.
Select Source: This dropdown allows you to specify the source field to evaluate.
Select Operator: Defines the logic operator (e.g.,
<=,>=,=,!=) to be applied to the source field.Result: Defines the outcome or action that should be taken when the conditions are met.
Add New Row: Allows you to add additional rules to the decision tree.
Example of a Decision Tree Configuration
This decision tree evaluates the Total Amount field and assigns it to different groups based on predefined conditions. Each rule compares the total amount against a specific value, and based on which condition is true, the corresponding Group is returned.
This decision tree evaluates two key conditions to determine which group should be assigned: Total Amount and Warehouse Status. The tree uses thresholds based on the total amount to define which group is returned, with the additional distinction of whether the warehouse is designated as "Warehouse Main," "Warehouse Sub," or "Not Warehouse Main."
Each rule is evaluated sequentially.
Decision Tree Policy
The Decision Tree Policy defines how multiple rules within a decision tree are processed. You can choose from several policies:
1. Unique Policy
Ensures that only a single rule is matched. If multiple rules are matched, the decision tree will return false.
Example:
1
Total Amount <= 1000
GROUP_1
2
Total Amount <= 2000
GROUP_2
3
Total Amount <= 5000
GROUP_5
4
Total Amount <= 4000
GROUP_4
5
Total Amount <= 3000
GROUP_3
If the total amount is 1500, the rules evaluated will be:
Rule 1: Total Amount <= 1000 (does not match)
Rule 2: Total Amount <= 2000 (matches)
Rule 3: Total Amount <= 5000 (matches)
Rule 4: Total Amount <= 4000 (matches)
Rule 5: Total Amount <= 3000 (matches)
Since multiple rules are matched (Rule 2, Rule 3, Rule 4, Rule 5), the decision tree will return false because the Unique policy ensures only one rule can match.
2. First Policy
The first matching rule is applied, and no further rules are evaluated.
Example:
1
Total Amount <= 1000
GROUP_1
2
Total Amount <= 2000
GROUP_2
3
Total Amount <= 5000
GROUP_5
4
Total Amount <= 4000
GROUP_4
5
Total Amount <= 3000
GROUP_3
If the total amount is 1500, the rules evaluated will be:
Rule 1: Total Amount <= 1000 (does not match)
Rule 2: Total Amount <= 2000 (matches) → The decision tree stops evaluating further rules and applies GROUP_2.
3. Priority Policy
Choosing this option allows you to set priorities for each rule. The lower the selected number, the higher the priority (i.e., priority 1 has the highest priority). Rules are evaluated based on their priority order. The highest priority matching rule will be applied.
Example:
1
5
Total Amount <= 1000
GROUP_1
2
4
Total Amount <= 2000
GROUP_2
3
3
Total Amount <= 3000
GROUP_3
4
2
Total Amount <= 4000
GROUP_4
5
1
Total Amount <= 5000
GROUP_5
If the total amount is 1500, the rules evaluated will be:
Rule 1: Total Amount <= 1000 (does not match)
Rule 2: Total Amount <= 2000 (matches)
Rule 3: Total Amount <= 3000 (matches)
Rule 4: Total Amount <= 4000 (matches)
Rule 5: Total Amount <= 5000 (matches)
Since the priority is applied in the order 5, 4, 3, 2, 1, the highest priority matching rule will be Rule 5 (GROUP_5). The decision tree will return GROUP_5 because Rule 5 has the highest priority (priority 1).
4. Collect (sum) Policy
This policy collects all matching rules and sums the results. It only works for Return Type Value.
Example:
1
Total Amount <= 1000
1
2
Total Amount <= 2000
2
3
Total Amount <= 3000
3
4
Total Amount <= 4000
4
5
Total Amount <= 5000
5
For the input value of Total Amount = 3500, the evaluation of rules would be:
Rule 1: Total Amount <= 1000 (does not match)
Rule 2: Total Amount <= 2000 (does not match)
Rule 3: Total Amount <= 3000 (matches, Return Value = 3)
Rule 4: Total Amount <= 4000 (matches, Return Value = 4)
Rule 5: Total Amount <= 5000 (matches, Return Value = 5)
Since the Collect (sum) policy is applied, we sum the Return Values of the matching rules, which are 3, 4, 5.
Summing these values gives:
5 + 4 + 3 = 12
Thus, the result returned by the decision tree would be 12, which is the sum of all matching return values.
5. Collect (min/max/count) Policy
This policy collects all matching rules and either selects the minimum, maximum, or counts the occurrences. It only works for Return Type Value.
Example:
1
Total Amount <= 1000
1
2
Total Amount <= 2000
2
3
Total Amount <= 3000
3
4
Total Amount <= 4000
4
5
Total Amount <= 5000
5
If the Collect (min) option is selected, the result will return the minimum of the Return Values for the matching rules.
For the input value of Total Amount = 3500, the evaluation of rules would be:
Rule 1: Total Amount <= 1000 (does not match)
Rule 2: Total Amount <= 2000 (does not match)
Rule 3: Total Amount <= 3000 (matches, Return Value = 3)
Rule 4: Total Amount <= 4000 (matches, Return Value = 4)
Rule 5: Total Amount <= 5000 (matches, Return Value = 5)
The matching rules are Rule 3, Rule 4, and Rule 5, with Return Values of 3, 4, and 5.
Since the Collect (min) policy is applied, the result will be the minimum value, which is 3.
Result: 3
If the Collect (max) option is selected, the result will return the maximum of the Return Values for the matching rules.
For the same evaluation as above, the result will be:
Result: 5
If the Collect (count) option is selected, the result will count the number of matching rules.
For the same evaluation as above, the result will be:
Result: 3 (since 3 rules matched).
6. Rule Order Policy
This policy applies rules in the order they appear in the decision tree and returns the result of the rule that matches first.
Example:
1
Total Amount <= 1000
GROUP_1
2
Total Amount <= 2000
GROUP_2
3
Total Amount <= 3000
GROUP_3
4
Total Amount <= 4000
GROUP_4
5
Total Amount <= 5000
GROUP_5
Given that the input value is Total Amount = 3500, the evaluation of the rules would be:
Rule 1: Total Amount <= 1000 (does not match)
Rule 2: Total Amount <= 2000 (does not match)
Rule 3: Total Amount <= 3000 (matches)
Rule 4: Total Amount <= 4000 (matches)
Rule 5: Total Amount <= 5000 (matches)
Under Rule Order, the tree will process the rules in the order they are listed. So, the matching rules will be:
Rule 3: GROUP_3
Rule 4: GROUP_4
Rule 5: GROUP_5
Result: GROUP_3, GROUP_4, GROUP_5
7. Any Policy
Multiple rules can be true, but the result of those rules must be the same.
Example:
1
Total Amount <= 1000
GROUP_1
2
Total Amount <= 2000
GROUP_2
3
Total Amount <= 3000
GROUP_3
4
Total Amount <= 4000
GROUP_4
5
Total Amount <= 5000
GROUP_5
If the total amount is 2500, the rules evaluated will be:
Rule 1: Total Amount <= 1000 (does not match)
Rule 2: Total Amount <= 2000 (does not match)
Rule 3: Total Amount <= 3000 (matches)
Rule 4: Total Amount <= 4000 (matches)
Rule 5: Total Amount <= 5000 (matches)
For Any to apply, all matching rules must return the same Return Group. Since the groups do not match across the different rules, the result would be false.
8. First & Adjacent Policy
Chooses the result of the rule that is adjacent to the first rule that is true.
Example:
1
Total Amount <= 1000
GROUP_1
2
Total Amount <= 2000
GROUP_2
3
Total Amount <= 3000
GROUP_3
4
Total Amount <= 4000
GROUP_4
5
Total Amount <= 5000
GROUP_5
If the total amount is 1500, the rules evaluated will be:
Rule 1: Total Amount <= 1000 (does not match)
Rule 2: Total Amount <= 2000 (matches)
Since Rule 2 is the first rule that matches, First & Adjacent would apply the result of Rule 3: GROUP_3.
Testing the Decision Tree
Overview: The decision tree designer includes a test feature to validate the logic of the configured rules. This feature allows users to test the decision tree by providing specific input values for the selected fields.
Steps to Use the Test Feature:
Locate the Test Button:
In the decision tree designer, find the Test button.
Open the Test Popup:
Click the Test button.
A popup window will appear, providing input fields corresponding to the criteria used in the decision tree.
Provide Input Values:
Enter values into the input fields to simulate a real-world scenario.
Evaluate the Results:
After entering the inputs, the tree processes them based on the chosen policy.
The system highlights the rule(s) that match the provided inputs.
Review Feedback for No Match:
If no rule is highlighted, the system will display feedback explaining why no rule matched.
Use this feedback to adjust inputs or review the tree's configuration for potential issues.
Export and Save
Save: Saves the current configuration of the decision tree.
Export: Allows you to export the decision tree configuration, which can then be imported into another environment or used for backup purposes.
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