WizWhy Description
WizWhy analyzes how the values of one data field are influenced by the values of other fields in the dataset. The analysis hinges on a dependent variable chosen by the user, while the remaining fields act as independent variables or conditions. This dependent variable can be examined in two ways: as a Boolean value or as a continuous measurement.
Users have the ability to refine their analysis by setting various parameters, including the minimum probability for rule formation, the least number of instances required for each rule, and the comparative costs associated with false negatives versus false positives.
WizWhy identifies and presents a series of rules that connect the dependent variable with other fields, expressing these rules using if-then and if-and-only-if constructs. Based on the identified rules, WizWhy highlights significant patterns, reveals unexpected rules that may indicate interesting phenomena, and points out unusual cases within the dataset. Additionally, WizWhy is capable of making predictions for new instances by leveraging the established rules.
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