Create a Rule Flow by Using Discovery Techniques

Create a Rule Flow by Using the New Discovery Wizard

About the Discovery Techniques

With the New Discovery wizard, you can use discovery techniques to generate business rule data and import that data into SAS Decision Manager. The discovery techniques that you can select from are:

Decision Tree

Decision Tree analysis produces a tree-like diagram in which each branch of the tree represents a possible decision or event. The tree structure shows how one choice leads to the next. Each branch represents a mutually exclusive option. Decision trees are often used for data segmentation or prediction modeling. You can create decision trees to classify observations based on the values of nominal, binary, or ordinal targets or to predict outcomes for interval targets.

Scorecard

Scorecards provide a quantitative score of the odds that a customer will display a defined behavior such as respond positively to a campaign, make a purchase, default on a loan, and so on. The higher the score, the more likely the defined behavior will occur. The SAS Decision Manager Scorecard uses the Weight of Evidence technique to generate scores.

Recency Frequency Monetary (RFM)

RFM is a technique that is used to identify existing customers who are most likely to respond to a new campaign or product offer. RFM analysis looks at when a customer last placed an order or bought something, how often the customer makes a purchase, and how much money they spend. Customers are assigned scores based on these factors.

Market Baskets

Market Basket analysis is used to predict items that are most likely to be purchased together. Market Basket analysis can be used to predict what items a customer is likely to buy.

Create a Rule Flow by Using the New Discovery Wizard

When you run the New Discovery wizard, it generates a vocabulary, as many rule sets as are needed, and a rule flow using the discovery technique that you select.

To create a rule flow using the New Discovery wizard:

Select the Business RulesRule Flows category.
Right-click on the folder where you want to create the new rule flow, and select New Rule Flow. Alternatively, select the folder where you want to add the new rule flow, click , and select New Rule Flow. The New Rule Flow window appears.
Enter a name for the new rule flow. Rule flow names are limited to 32 characters and can contain any character except forward slash (/), backslash (\), left brace ({), right brace (}), colon (:), and question mark (?).

Note: The name that you enter is used for both the vocabulary and the rule flow. Vocabulary names must be unique within the rules database.
(Optional) Enter a description for the new rule flow. Descriptions are limited to 256 characters.
(Optional) Select Create output only for records that fire rules to limit the output of the rule flow. By default, all output records are written to the output data set. However, for some types of applications, only the output records for which at least one rule has fired are of interest. Limiting output is useful for applications that detect outliers, such as applications that detect fraud.
Select Use discovery techniques to generate rules.
Click Create. SAS Decision Manager opens the New Discovery window.
Select the Discovery technique. The techniques that are available depend on the products that are licensed at your site. The Recency Frequency Monetary (RFM) technique is available with Base SAS. The Decision Tree and Scorecard techniques require a SAS/STAT license. The Market Baskets technique requires a SAS Enterprise Miner license.
Select the Data source that you want to use for the discovery analysis.
Select the setup options for the discovery technique, and click Next. The setup options depend on the technique. See Setup Options and Terms For Discovery Techniques.
Select the terms required for the discovery technique. See Setup Options and Terms For Discovery Techniques.
Click Run to run the analysis. SAS Decision Manager displays the rule sets that were generated by the analysis.
Click Import to import the data. If the data was imported successfully, SAS Decision Manager displays a confirmation message telling you what data was imported and which folder it was added to.
(Optional) Click Rule_generation_log and Rule_import_log to download the log files to your local machine. The log file name is RuleFlowName_generation.log, and the import log file name is RuleFlowName_import.log. If rules can not be generated or the import process fails, the log files contain detailed error messages.
Click Close to close the New Discovery wizard. SAS Decision Manager opens the new rule flow in the rule flow editor and displays the Rule Sets page.

After using the New Discovery wizard to generate and import a new rule flow, all of the rule set versions in the rule flow will be unlocked, latest versions. To publish the rule flow, you must lock the rule sets, and then select the locked version in the rule flow editor. See Lock a Rule Set Version and Step 11 in Create a Rule Flow Using the Rule Flow Editor for more information.

Setup Options and Terms For Discovery Techniques
Discovery Technique	Setup Variables	Terms
Decision Tree	Maximum number of rules: Select the maximum number of rules that you want to be generated from the discovery analysis.	Select the terms whose values you want to predict, and click to move them to the Actions list.
Scorecard	Minimum points: The scorecard points are scaled with this option as the minimum value. You can specify any non-negative integer. Maximum points: The scorecard points are scaled with this option as the maximum value. You can specify any positive integer that is greater than the Minimum points value.	Target variable: specifies the variable that you are modeling. The variable must have exactly two discrete values such as `0` and `1` or `True` and `False`. Target category: specifies how the values of the target variable are mapped. The scorecard points are scaled to the likelihood of the two target variable values based on the sort order. Select High to indicate that the highest lexical value of the target variable is mapped to the Maximum points value. Select Low to indicate that the lowest lexical value of the target variable is mapped to the Maximum points value.
Recency Frequency Monetary	Select the binning method. Independent: Simple ranks are assigned to recency, frequency, and monetary values. The three ranks are assigned independently. Nested: A simple rank is assigned to recency values. Within each recency rank, customers are then assigned a frequency rank. Within each frequency rank, customer are assigned a monetary rank.	Customer ID: specifies a numeric or character term that uniquely identifies a customer. Transaction date: specifies the transaction date. Transaction amount: specifies the transaction amount.
Market Baskets	Maximum number of rules: Select the maximum number of rules that you want to be generated from the discovery analysis.	ID: specifies the customer ID. Item: specifies the item that was purchased.